Lead Data Engineer
Primary Skills
- Athena, Step Functions, Spark – Pyspark, ETL Fundamentals, SQL (Basic + Advanced), Glue, Python, Lambda, Data Warehousing, EBS /EFS, AWS EC2, Lake Formation, Aurora, S3, Modern Data Platform Fundamentals, PLSQL, Data Modelling Fundamentals, Cloud front
Specialization
- AWS Data EngineerIng Basic: Data Specialist
Job requirements
- Data Product Engineer An experienced Data Product Engineer with 5+ years of hands-on expertise in building, delivering, and supporting data-driven solutions that serve both operational and analytical customers. Adept at translating raw data into actionable insights and production-ready data products, ensuring scalability, security, and integration with modern digital ecosystems. Core Responsibilities: Collaboratively build, maintain, and monitor high-quality Data Products for diverse customer needs. Act as a subject matter expert, with strong understanding of both technical and business aspects of data. Ensure compliance with data security standards while maintaining clear documentation and knowledge sharing. Apply Software Engineering principles (CI/CD, Git, TDD, DOD, Agile) to data workflows for seamless ecosystem integration. Manage end-to-end data lifecycle: ingestion, transformation, storage, and provisioning. Technical Skillset: Data Engineering & Analytics: Data pipelines, ETL/ELT, data modeling, analytics, and visualization. Cloud Platforms: AWS: S3, Redshift, Athena, Lambda, Glue, CodePipeline, CloudFormation, sns.microsoft Azure & Google Cloud (working knowledge). Data Tools & Frameworks: SSIS, Databricks, Spark, SQL, Python, R, Scala. Databases: SQL Server, DynamoDB, ArangoDB. File Formats: JSON, XML, Parquet, CSV. Visualization & Exploration: QuickSight, Tableau, Excel Collaboration & Documentation: Miro, Confluence. Core Competencies: Product Thinking with customer-centric mindset. Strong planning, communication, and organizational skills. Proficient in version control (Git/GitHub), CLI scripting (Bash, PowerShell, AWS CLI). Agile and Test-Driven Development mindset. Familiarity with modern data management concepts (Data Mesh, Event Streaming).
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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