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Social Discovery Group (SDG) is a group of social discovery companies. SDG solves the problems of loneliness, isolation, and disconnection - transforming virtual intimacy into the new normal. SDG’s products redefine the way people interact and connect with one another. Our portfolio includes social entertainment platforms designed to connect people online across different cultures and regions of the world. We bring together a team of like-minded people and IT professionals who specialize in creating and developing globally impactful social discovery products. Our international team of digital nomads works remotely from all over the world. We’re proud to be a two-time “Great Place to Work” winner (USA & Japan, 2024–2025) and a Top-5 Company for Work-From-Anywhere Jobs (FlexJobs, 2025). We are looking for Head of Supply . Your main tasks will be: • Own the supply side of a two-sided marketplace: keep demand covered by quality, available supply at a sustainable cost. • Build the supply planning system: demand forecasting, a sufficiency model and partner order plans, with control over how they're carried out. • Manage the supply–demand balance across segments, time slots and formats, separating registered supply from available supply. • Lead three areas: Partner Support (automation), Partners Development & Growth (mid-size partners) and Key Partners Success (top 50). • Design partner economics and incentives: payouts, commissions, bonuses and the Bronze Silver Gold Platinum tier system, with safeguards against gaming the rules. • Own quality and trust: tie partner communication quality to customer retention and stop harmful practices. • Drive change from hypothesis to pilot to scaled process, working with analytics and product on cohorts and control groups. We expect from you: • Supply/demand analysis by segment, time slot and format, including setting forecasting tasks for analysts. • Partner unit economics: payouts, cost to serve, payback, revenue split. • Incentive design: commissions, bonuses, rules and anti-gaming mechanisms. • Experience running partner tier systems and the economics of moving partners up the tiers. • Partner segmentation, account management and development planning. • Operational management: SLAs, quality standards, deviation analysis, process automation. • Experiment design and impact measurement: cohorts, control groups, and separating the effect of your own decisions from traffic or product changes. What do we offer: • REMOTE OPPORTUNITY to work full-time; • The initial pay level or pay range for this role will be shared with candidates during the recruitment process and before the commencement of employment; • Vacation 28 calendar days per year; • 7 wellness days per year (time off) that can be used to deal with household issues, to lie down and recover without taking sick leave; • Bonuses up to $5000 for recommending successful applicants for positions in the company; • 50% payment for professional training, international conferences, and meetings; • Corporate discount for English lessons; • ​ Health benefits. According to the paychecks, if you are not eligible for corporate medical insurance, the company will compensate you with up to $ 1,000 gross per year per employee. This can be spent on self-purchase of health insurance or on doctor’s fees for yourself and close relatives (spouse, children); • ​ Workplace organization. The company provides all employees with an equipped workplace and all the necessary equipment (table, armchair, wifi, etc.) in our offices or co-working locations. In the other locations, the company provides reimbursement of workplace costs up to $ 1000 gross once every 3 years, according to the paychecks. This money can be spent on the rent of the co-working room, on equipping the working place at home (desk, chair, Internet, etc.) during those 3 years; • Internal gamified gratitude system: receive bonuses from colleagues and exchange them for our merchandise, team building activities, massage certificates, etc. Sounds good? Join us now! Originally posted on Himalayas

Szukamy osoby na stanowisko Senior Cloud Data Engineer z doświadczeniem w pracy z chmurą AWS oraz Databricks. Projekt obejmuje stworzenie rozwiązania typu lakehouse, przygotowanie prototypu prezentowanego podczas wydarzenia branżowego, a następnie realizację pilotażowego wdrożenia i dalszy rozwój platformy. Poszukujemy osoby, która będzie aktywnie wspierać zarówno architekturę, jak i implementację rozwiązania, współtworząc fundamenty skalowalnej platformy danych wykorzystywanej do zaawansowanej analityki oraz raportowania biznesowego. Projekt realizowany jest w oparciu o nowoczesny ekosystem Databricks, medallion architecture oraz najlepsze praktyki Data Engineering. Optymalny start współpracy: listopad 2026 Szukamy Ciebie, jeśli: • masz min. 5 lat doświadczenia w IT, w tym min. 3,5 roku w komercyjnej pracy z danymi w chmurze AWS (Glue, Athena, DynamoBD), • masz doświadczenie w pracy z narzędziem Terraform , • masz doświadczenie w pracy z Databricks , • masz komercyjne doświadczenie w przetwarzaniu sporych danych przy użyciuJSON, • znasz i wykorzystujesz Python oraz PySpark, • korzystasz z SQL na poziomie zaawansowanym i wykorzystujesz go na rozwiązaniach technologicznych MS i nie tylko, • znasz metodyki i stosujesz biegle Git oraz CI/CD, • posiadasz doświadczenie z dbt , • tworzysz i optymalizujesz rozwiązania przetwarzające dane (ETL, ELT, itp.) poprzedzone projektem technicznym oraz alternatywami rozwiązań (np. Apache Airflow) • masz doświadczenie z praktykami zwinnymi oraz znasz narzędzia wykorzystywane w procesie wytwarzania oprogramowania, w tym np. Azure DevOps, • masz wiedzę na temat stosowania mechanizmów związanych z bezpiecznym przechowywaniem i przetwarzaniem danych w chmurze, • świadomie wykorzystujesz Generative AI w procesie wytwarzania oprogramowania oraz w decyzjach architektonicznych i technologicznych, • posługujesz się j. angielskim na poziomie średniozaawansowanym (min. B2) oraz swobodnie komunikujesz się w języku polskim. Praca na tym stanowisku w naszej firmie oznacza: • projektowanie i rozwijanie nowoczesnej platformy danych opartej na Databricks i AWS , • budowę oraz optymalizację procesów ETL/ELT wykorzystujących PySpark, Spark SQL i dbt, • implementację architektury lakehouse zgodnie z podejściem medallion (Bronze, Silver, Gold), • współtworzenie standardów dotyczących Data Engineering, jakości danych i Data Governance, • wdrażanie oraz rozwój rozwiązań opartych o Unity Catalog , • projektowanie modeli danych wspierających potrzeby analityczne i raportowe biznesu, • współpracę z architektami, analitykami i klientem przy definiowaniu kierunku rozwoju platformy,integrację danych z wielu źródeł oraz implementację mechanizmów CDC i near-real-time data processing, • aktywny udział w przygotowaniu i prezentacji prototypów produktu, • wpływ na decyzje architektoniczne oraz rozwój strategicznej platformy danych od wczesnych etapów jej powstawania. Doświadczenie • 5 lat Wynagrodzenie_senior • 133 – 196 zł/h netto + VAT (B2B) Typ oferty • Data Solutions Technologie • AWS • Python • SQL • Databricks Co oferujemy, by pracowało Ci się dobrze: • dużą swobodę działania i realny wpływ na kierunek projektów, • projekty dla klientów z Europy i USA – branża turystyczna, ubezpieczeniowa, energetyczna, farmaceutyczna i finansowa, • certyfikacje i szkolenia chmurowe: AWS, Microsoft, Databricks Academy – opłacamy szkolenia i egzaminy, • narzędzia AI dla każdego w zespole od pierwszego dnia, • społeczność ekspertów: grupy tematyczne, dostęp do zespołu architektów systemowych, analityków biznesowych i zespołu UX, • możliwość pracy 100% remote, • damy Ci merytoryczny feedback po zakończonym procesie rekrutacyjnym – niezależnie od wyniku. • Więcej o zespole, projektach i technologiach: • Case study: Język • angielski B2+ Originally posted on Himalayas

• Participate in the migration of a large-scale analytical platform from BigQuery to Databricks • Design and implement scalable Lakehouse architectures using Databricks and Delta Lake • Analyze existing ETL / ELT workloads and define migration approaches • Develop and optimize data pipelines processing large volumes of retail and analytical data • Implement incremental processing strategies and scalable transformation frameworks • Build and maintain Spark-based data processing solutions using PySpark • Design and maintain medallion architecture layers including Bronze, Silver, and Gold • Implement data governance and security best practices using Unity Catalog • Collaborate with Data Science, Analytics, Product, and Customer Engineering teams • Participate in architecture discussions and technical solution design • Develop reusable data platform components and engineering standards • Conduct code reviews and contribute to platform reliability and maintainability • Troubleshoot and optimize complex SQL and Spark workloads • Support production deployments and platform modernization activities • 5+ years of professional experience as a Data Engineer • Strong programming skills in Python and advanced SQL • Hands-on commercial experience with Databricks • Strong knowledge of Apache Spark, primarily PySpark • Experience designing and building modern cloud-based data platforms • Experience developing ETL / ELT pipelines and large-scale data processing solutions • Hands-on experience with Delta Lake • Experience with Spark Declarative Pipelines • Experience with cluster monitoring, metrics analysis, and performance optimization • Strong understanding of distributed data processing architectures • Solid understanding of data warehousing concepts and dimensional modeling • Experience with Airflow or similar orchestration tools • Experience optimizing complex analytical SQL workloads • Experience implementing CI / CD practices for data engineering platforms • Strong troubleshooting and performance optimization skills • Ability to work collaboratively in cross-functional international teams • Upper-Intermediate or higher English level WILL BE A PLUS • Experience working with GCP cloud services • Experience with AWS or Azure cloud platforms • Experience in retail analytics or pricing optimization domains • Experience supporting machine learning or AI-related data workloads • Experience with platform modernization and cloud migration initiatives PERSONAL PROFILE • Strong analytical and problem-solving mindset • Proactive and ownership-driven approach • Ability to work independently and collaboratively • Good communication and stakeholder collaboration skills • Passion for scalable data engineering and modern data platforms • Interest in continuous learning and technology innovation Are you a Senior Data Engineer passionate about building scalable, high-performance data platforms and working with modern Lakehouse technologies? Join Sigma Software’s Data Engineering Center of Excellence and contribute to the modernization of an enterprise-scale analytics ecosystem for the retail domain. We are looking for a Senior specialist with strong Databricks, PySpark, and cloud data engineering expertise to participate in the migration of a large-scale analytical platform from BigQuery to Databricks. You will collaborate with international teams, contribute to architectural decisions, and help shape reliable and scalable data solutions. We at Sigma Software create opportunities for continuous learning, technology growth, and meaningful engineering impact while working on complex international projects. CUSTOMER Our Customer is a leading retail technology company specializing in AI-driven pricing optimization solutions for enterprise retailers. The company helps businesses improve profitability and competitiveness through advanced analytics, automation, and intelligent pricing strategies. Their platform combines business intelligence with sophisticated algorithms to support data-informed pricing decisions at scale for global retail organizations. PROJECT The project focuses on the strategic migration of a large-scale analytical platform from a legacy BigQuery ecosystem to a modern Databricks Lakehouse architecture. The platform processes high-volume retail datasets, machine learning workloads, analytics pipelines, and customer-specific business logic. As part of the modernization initiative, the engineering team is implementing scalable Spark-based processing, Delta Lake architecture, medallion data layers, and modern governance practices. The role offers an opportunity to work with distributed data processing systems, optimize large-scale workloads, and contribute to the evolution of an enterprise-grade data platform. Key Technologies: Databricks, Apache Spark, PySpark, Delta Lake, Python, SQL, Airflow, GCP, CI/CD, Unity Catalog

payabl. empowers businesses to grow through payments innovation and banking services. Our ambition is to expand our strong portfolio of global financial services we provide to businesses and make them all available in one place on our platform we call payabl.one. As a licensed financial company with principal membership with card schemes, we specialize in global payments and providing businesses with multi-currency accounts. The role is about: Working as part of our Data Team to build and maintain reliable data pipelines and datasets that support analytics and decision-making across the organization. You will work with SQL, Python, cloud data platforms, batch and streaming pipelines, and modern data engineering technologies. You will collaborate with engineers, analysts, and business teams to understand data requirements, improve data quality, and make data easier to consume. We are looking for someone with strong data engineering fundamentals who is curious, enjoys solving problems, and is interested in developing their skills across modern data platform technologies. Location: Remote – Poland or Portugal | On-site – Cyprus Reporting to: Head of Engineering What you will do: Data Pipelines and Data Platform • Build and maintain reliable ETL/ELT data pipelines using SQL and Python. • Develop and maintain datasets used for analytics, reporting, and other business use cases. • Work with batch and streaming data pipelines running on AWS. • Contribute to the continuous improvement of our data platform, architecture, and engineering practices. Data Modelling and Business-Ready Data • Work with analysts, engineers, and business teams to understand data requirements and translate them into technical solutions. • Develop well-structured and reusable datasets that make data easier to consume across the organization. • Support data transformations and data modelling for analytics and reporting use cases. • Contribute to improving the consistency, usability, and reliability of business data. Data Quality and Production Reliability • Support data quality checks and validation processes to ensure reliable and consistent datasets. • Monitor data pipelines and help identify and troubleshoot data or pipeline issues. • Support production reliability and investigate issues when pipelines or datasets do not behave as expected. • Contribute to improvements in monitoring, observability, documentation, and data reliability practices. Batch and Streaming Processing • Work with batch and streaming data pipelines across the data platform. • Support data processing and transformation workflows running on cloud-based infrastructure. • Contribute to the development and maintenance of scalable and reliable data processing solutions. Data Integration and Platform Development • Work with data from relational and non-relational databases and other internal or external data sources. • Support integrations and data ingestion workflows across different systems. • Contribute to the evolution of the data platform as new requirements and technologies are introduced. What we need: • 3+ years of experience in data engineering, software engineering, analytics engineering, or a related role. • Good programming skills in Python and SQL. • Experience building or maintaining ETL/ELT pipelines. • Experience working with relational and non-relational databases such as MySQL, MariaDB, PostgreSQL, MongoDB or similar. • Familiarity with cloud-based data platforms, preferably AWS. • Understanding of basic data engineering concepts such as incremental processing, data quality, schema changes, and pipeline reliability. • Comfortable working with Git and Unix/Linux environments. • Good problem-solving and debugging skills. • Willingness to learn new technologies and work across different parts of the data platform. Good to Have You do not need experience with all of the technologies below. Experience with one or more would be beneficial: Data Processing and Cloud • You do not need experience with all of the technologies below. Experience with one or more would be beneficial: • Data Processing and Cloud • Apache Spark or PySpark. • AWS services such as S3, Glue, EMR, IAM, or Athena. • Data lake or lakehouse architectures. • Apache Iceberg, Delta Lake, Hudi, or another open table format. Streaming and Data Integration • Apache Kafka or another streaming platform. • Change Data Capture concepts or tools such as Debezium. • Airbyte or other data integration platforms. Orchestration and Data Architecture • Apache Airflow, Dagster, or another workflow orchestration tool. • Medallion architecture concepts such as bronze, silver, and gold data layers. • DBT or experience working with analytics engineering teams. Infrastructure and Engineering • Terraform, Terragrunt, or other infrastructure-as-code tooling. • Docker or Kubernetes. • Data quality, observability, monitoring, lineage, or governance tooling. …

What is Jedox? At Jedox, we help businesses plan for a better future. Our Enterprise Performance Management (EPM) software empowers finance, sales, and other departments to budget, forecast, and analyze data—all in one intuitive platform. We’re on a mission to turn complex planning into #Superplännen: that amazing moment when everything goes exactly as you envisioned it. Your Responsibilities As a Data engineer, you will be responsible for designing, developing and operating our enterprise data platform. Your role will involve ensuring that data is integrated, governed and AI-ready, thereby creating the backbone for all intelligent applications and insights across the business. • Design and own the enterprise data platform: Build a scalable Microsoft Fabric data infrastructure using a medallion lakehouse architecture (Bronze, Silver or Gold) with Delta Lake. • Develop and operate data pipelines: Create robust batch and streaming ETL/ELT pipelines with schema evolution, automated transformation and strong data quality validation. • Integrate enterprise systems: Connect to data sources such as SharePoint, Salesforce, Microsoft 365, Azure SQL, ERP/CRM systems, file repositories and REST APIs. • Ensure performance and reliability: Optimize storage and processing across structured and unstructured data, including monitoring, alerting, and operational stability. • Build semantic data layers & governance: Establish a taxonomy and metadata standards, as well as semantic models and data cataloguing and lineage tracking. Enforce access control, compliance and security. • Drive AI readiness: Prepare data for AI use cases through document chunking, embedding pipelines, and vector-ready datasets for RAG. • Expose knowledge services & collaborate: Develop reusable APIs and data services for AI applications and work cross-functionally with AI, analytics, and business teams (#OneTeam). Your Profile • 7+ years in data engineering, including 3+ years building enterprise-scale cloud platforms, with proven greenfield architecture and AI/ML data preparation experience. • Expertise in Python and SQL, and I have hands-on experience with Spark, Microsoft Fabric, the Azure Data Platform and Delta Lake. I am also experienced in ETL/ELT, data modelling and warehousing. • Experience integrating enterprise systems (e.g., Salesforce, SharePoint, M365, Azure SQL/Data Lake) and working with REST APIs and modern data architectures. • Solid understanding of metadata management, master data management, and semantic modelling. • Certifications in Azure/Fabric and experience with Purview, Synapse, Data Mesh, graph/vector databases, Azure AI Search, or event streaming. • Growth-oriented, proactive and driven by innovation, execution excellence and building impactful, scalable data solutions. • Excellent English communication skills are required Transparency Note: Use of Artificial Intelligence As a tech-driven company, Jedox uses modern technologies — including AI — to continuously improve our processes. In recruiting, AI may support us in screening and structuring applications. It does not replace human judgment, but helps us reduce bias and ensure a consistent candidate experience. Your application is always reviewed by real people. If you would like to learn more about the process, please visit the website of our partner Hi People . Here you will find information about the data protection guidelines as well as the most recent security checks. This gives you complete clarity on how your data is protected and processed. Of course, you can also contact us at any time if you have any questions.