Data Engineer II leading development and delivery of data pipelines for Syneos Health. Collaborating with teams to optimize data processing and integrate solutions into production environments.
About the role
- Senior Data Engineer designing and scaling data pipelines for high-volume ecosystems. Join Yora's mission to impact technology positively in autonomous systems and AI.
Responsibilities
- Architect and Scale end to end data pipelines from ingestion to transformation across batch and Streaming systems.
- Processing billions of sensor, simulation and telemetry events daily.
- Partner with AI, ML, and simulation teams to deliver ML-ready, traceable, and compliant datasets.
- Work hands-on with tools like Airflow, Spark, Databricks, and cloud platforms such as GCP or Azure.
- Lead data governance initiatives: schema evolution, data cataloging, and proactive pipeline monitoring.
- Enable AI workflows with efficient data selection, annotation, labeling pipelines, and feedback loops.
- Design and enforce best practices around data observability and data protection
Requirements
- 3+ years’ experience building and running scalable, resilient data pipelines in production.
- Strong Python and SQL skills, plus hands-on cloud expertise (GCP, Azure, AWS).
- Experience with orchestration tools like Airflow, Dagster or Perfect2
- Experience with Apache Spark, Apache Flink, Kafka, Databricks, or similar data engineering tools.
- Solid understanding of data architecture trade-offs — latency, throughput, cost, and storage formats like Parquet and Avro.
- A passion for data quality, reproducibility, and building maintainable systems, not just “moving data.”
- Bonus Points
- Experience with sensor data, telemetry, or real-time time-series data.
- Familiarity with cloud data warehouse (Snowflake, BigQuery)
- Familiarity with ML/AI infrastructure like feature stores, labeling pipelines, or MLOps tooling.
- Knowledge of CI/CD, Infrastructure as Code( Terraform), containerization (Docker/Kubernetes), and versioning of data and pipelines.
Benefits
- Flexible working — hybrid in Gothenburg or fully remote within the EU
- Opportunity to influence the future of large-scale data engineering in industries like autonomous systems
- Join a highly collaborative team of ML, simulation, and data experts
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