Build new and maintain existing integrations to third-party billing and usage APIs, own pipeline orchestration/scheduling/backfill, ensure data correctness (deduplication, reconciliation, normalization), work AI-augmented, and collaborate with product and support. Requires strong SQL, Python, experience with orchestration frameworks (Dagster/Airflow preferred), and familiarity with cloud data warehouses (BigQuery/ClickHouse/Snowflake/Redshift).

DoiT is hiring a remote Data Engineer to expand vendor coverage for cloud and SaaS spend by building integrations against third-party billing and usage APIs, owning ingestion pipelines (orchestration, scheduling, backfills), ensuring data correctness and normalization, and using AI-augmented workflows. The role targets candidates with 3+ years in data engineering or data-heavy backend roles, strong SQL and Python skills, experience with orchestration tools (Dagster/Airflow or equivalents), and familiarity with cloud analytical stores (BigQuery, Snowflake, ClickHouse, Redshift, etc.). The position is open to full-time employees in the UK, Ireland, Estonia, the Netherlands, Sweden, and Israel; contractors are also considered in Eastern Europe and Portugal.

The Data Engineer will build and maintain integrations with third-party billing and usage APIs, own end-to-end ingestion pipelines (orchestration, scheduling, backfills), and ensure data correctness and normalization across vendors. Requires 3+ years in data engineering or data-heavy backend roles, strong SQL and Python, experience with orchestration frameworks (Dagster/Airflow or equivalent), cloud analytical stores (BigQuery/Snowflake/ClickHouse/Redshift), and experience integrating REST APIs.

Hiring a Data Engineer to build and maintain integrations with third-party billing and usage APIs, own end-to-end ingestion pipelines (orchestration, scheduling, backfills), ensure data correctness and normalization across vendors, and use AI-augmented workflows. Requires 3+ years in data engineering or data-heavy backend roles, strong SQL and Python, experience with orchestration frameworks (Dagster/Airflow) and cloud analytical stores.

Full-time remote Data Engineer responsible for building and maintaining integrations against third-party billing and usage APIs, operating end-to-end ingestion pipelines (orchestration, backfills), ensuring data correctness (deduplication, reconciliation, normalization), and using AI-augmented tooling. Requires 3+ years of data engineering or data-heavy backend experience and strong SQL and Python skills.

DoiT is hiring a Data Engineer to expand vendor coverage and build integrations against third-party billing and usage APIs, own ingestion pipelines (orchestration, scheduling, backfills), ensure data correctness and normalization across vendors, and work with AI-augmented tooling. Requires 3+ years in data engineering or data-heavy backend roles, strong SQL and Python, experience with orchestration frameworks (Dagster/Airflow preferred), cloud data warehouses (BigQuery/ClickHouse/Snowflake/Redshift or similar), and API integration experience. Role is remote and available as a full-time employee in the UK, Ireland, Estonia, the Netherlands, Sweden, Israel, and contractors considered in Eastern Europe and Portugal.

Lead strategic engineering initiatives to improve how product teams build, operate, and evolve services on Datadog's Observability Data Platform. Design and build scalable platform capabilities (including cost intelligence, operational intelligence, self-service tooling, and reusable services), provide technical leadership and mentorship across teams, participate in on-call rotation, and drive platform reliability and observability. Requires experience with large-scale SaaS/cloud platforms, distributed systems, and backend technologies such as Java and Go; familiarity with Kafka and Kubernetes is mentioned.

Lead a small senior Data team and the emerging ML function, owning end-to-end delivery of streaming, warehouse modelling, and pipelines; coach and grow engineers; ensure operational excellence (data quality monitoring, incident response, post-mortems); and embed FinOps practices. Role is remote-first with candidates listed for the UK, Hungary, Poland, South Africa, Portugal, Ireland, and Romania.

Primer is hiring a Data Engineer III to design and build reliable, tested, maintainable data systems that support analytics, product features and machine learning. The role works with Python and SQL across batch and streaming (including CDC) pipelines, modern data warehouses (Snowflake), transformation tooling (dbt), and cloud-native infrastructure (AWS, Kubernetes, Helm, Terraform). The position is remote-first and listed for candidates in the UK, Hungary, Poland, South Africa, Portugal, Ireland and Romania.

Responsible for Primer's GTM intelligence layer—maintaining dashboards, semantic data models, and the BI tool's AI. The role includes modelling Salesforce data, building signals and forecasting models, partnering with data engineering to close data gaps, and driving adoption, training, and impact measurement. Requires hands-on SQL, experience with AI/LLMs and integrations, and ~3+ years in analytics/BI/RevOps.

Datadog seeks a Senior Software Engineer for REDAPL, its Referential Data Platform, to drive architecture and implementation of high-scale data ingestion, processing, and query pipelines (including a graph/query engine). The role involves leading technical projects, collaborating with product teams, and improving platform performance, cost efficiency, and resilience. Experience with distributed systems, backend/platform engineering, and graph databases or query engines is emphasized.

Manager role responsible for the architecture and roadmap of Kraken's real-time streaming and data platform (Spark, Kafka, Iceberg, RisingWave, Flink), building scalable data systems for trading, risk, compliance and analytics. Requires 8+ years in data/platform/distributed systems (with 3+ years managing teams), experience with AWS data services, production streaming/CDC pipelines, programming in Python/Scala/Java, and adoption of AI automation in data workflows.

Veeva is hiring a Manager, Data Operations to lead a Data Operations team for Veeva Link. Responsibilities include managing a team (5 Veevans + many curators), improving processes, ensuring data quality, guiding Data Analysts, and partnering with cross-functional teams. Requirements include 5+ years of people leadership, strong spreadsheet skills, data-driven decision-making, and excellent English communication. Nice-to-haves include life sciences experience and skills with SQL/Tableau. Total compensation range listed: 40,000 - 60,000 EUR.

Lead a team of 6-8 data analysts responsible for configuring crawlers to extract website data, ensuring data quality and timely delivery to the data platform. Role requires 3+ years leading technical teams, hands-on experience building scalable crawlers, knowledge of version control and code reviews, and familiarity with Python-based data processing. Total compensation listed: 80,000 - 150,000 EUR.

Lead a remote team (50+ headcount) working on Veeva OpenData in Lisbon/Portugal. Own team KPIs and performance, design and optimize data production processes, implement quality and efficiency projects, collaborate with engineering on automation, and escalate risks and incidents. Compensation range: 25,000–38,000 EUR (total).

The Data Operations Lead will manage and mentor a remote team of Data Curators responsible for Veeva OpenData, owning data quality standards, designing scalable processes, driving automation initiatives with Product and Engineering, monitoring KPIs, and addressing data risks. Requires 3+ years working with complex data sets or data operations, strong process design experience, leadership/mentoring experience, and excellent written and verbal English.

Prezi is hiring a Senior Data Analyst to join the Data Science & Analytics team (remote across listed European countries). The role involves end-to-end analyses (requirements, data processing, presentation), building dashboards and data products, defining metrics, quantifying impact, fostering self-service analytics, and collaborating with data engineering. Required: 5+ years in data/business analytics, proficiency in SQL and Python (or other scripting), experience with statistical analyses (funnel analysis, clustering, forecasting, recommender systems), dashboard building, strong English communication, and interest/experience in AI tools. Bonus experience: AWS, ETL pipelines, SaaS analytics, personalization/recommendation work.