Senior Data Engineer

This is a fully remote position, open to applicants in Poland.

📋 Description

• Take charge of the complete architecture for contemporary, cloud-native data platforms.

• Architect scalable data ecosystems utilizing data mesh, data products, and data contracts.

• Make impactful architectural choices across the ingestion, storage, processing, and access layers.

• Guarantee that platforms are secure, compliant, and designed for production readiness.

• Design and implement cloud-native data platforms leveraging Databricks, Snowflake, AWS, and GCP.

• Employ modern architectural patterns: data mesh, data products, and data contracts.

• Integrate thoroughly with client systems to facilitate scalable, consumer-centric data access.

• Construct and enhance batch and real-time pipelines.

• Work with streaming and event-driven technologies such as Kafka, Flink, Kinesis, Pub/Sub.

• Orchestrate workflows utilizing Airflow, Dataflow, Glue.

• Process and transform substantial datasets using Spark and Flink.

• Develop systems that perform effectively in production, not just theoretically.

• Operate across relational, NoSQL, and analytical databases (Postgres, BigQuery, Snowflake, Cassandra, MongoDB).

• Optimize storage formats and access patterns (Parquet, Delta, ORC, Avro).

• Implement secure, compliant data solutions with a focus on security by design.

• Incorporate governance without hindering developer efficiency.

• Collaborate directly with clients to comprehend challenges and formulate solutions.

• Convert business requirements into practical engineering decisions.

• Serve as a reliable technical advisor rather than merely following orders.

• Establish engineering standards, patterns, and best practices across teams.

• Review designs and code, offering clear technical guidance and mentorship.

• Elevate standards for data quality, testing, observability, and operational excellence.

⛳️ Requirements

• Proficient in Python and SQL.

• Extensive experience with Spark and modern data platforms (Databricks / Snowflake).

• Solid understanding of cloud data services (AWS or GCP).

• Proven ownership of large-scale data platform architectures.

• Strong skills in data modeling and architectural decision-making.

• Capable of balancing trade-offs among performance, cost, and complexity.

• Experience in building and operating large-scale data pipelines in production environments.

• Strong data modeling capabilities and architectural judgment.

• Familiarity with various storage technologies and formats.

• Experience with infrastructure-as-code tools (Terraform, Pulumi).

• Proficient in CI/CD pipelines using tools like GitHub Actions, ArgoCD.

• Knowledge of data testing and quality frameworks (dbt, Great Expectations, Soda).

• Background in consulting or professional services settings.

• Strong consulting instincts — capable of challenging assumptions and guiding clients to improved outcomes.

• Comfortable mentoring senior engineers and influencing technical culture.

🏝️ Benefits

• Engage with interesting, high-impact challenges.

• Create modern platforms, rather than managing outdated systems.

• Collaborate with senior engineers who truly excel in their fields.

• Enjoy autonomy, influence, and opportunities for professional growth.