Senior Data Engineer AWS & GCP
Remote · Brazil or Portugal
Job Summary
Senior Data Engineer role focusing on end-to-end data pipeline design and optimization using Databricks and cloud services (AWS/Azure/Google Cloud). Responsibilities include building robust ETL/ELT workflows, data ingestion and transformation, data modeling and architecture, ensuring data quality and governance, collaborating with cross-functional teams, and contributing to CI/CD and automation initiatives. Requires strong Python/Scala/SQL and Spark experience, distributed data processing, and ability to communicate complex technical concepts to non-technical stakeholders.
Required Qualifications
- Approximately 4 years of experience in data engineering for mid-level roles
- 6 or more years of experience for senior-level data engineering positions
- Between 1 to 4 years of experience building data products using platforms such as Databricks, Spark, Cloudera, or HortonWorks
- Skilled in Python (especially PySpark), Scala, and SQL
- Experienced in designing and implementing scalable data pipelines for high-volume environments
- Solid understanding of ELT/ETL practices and data integration strategies
- Capable of writing robust production code with automated testing
- Familiar with CI/CD tools such as GitHub Actions and Jenkins for deploying code
- Hands-on experience with distributed data processing using Apache Spark
- Proficient with cloud services including AWS, Azure, or Google Cloud and tools like S3, Glue, Lambda, Redshift, and BigQuery
- Good knowledge of data modelling, relational databases, and SQL performance optimisation
- Strong analytical and problem-solving abilities, with attention to troubleshooting details
- Effective communicator with experience working in collaborative, cross-functional teams
- Basic understanding of machine learning concepts such as classification, regression, A/B testing, and experimental design
- AWESOME BUT NOT REQUIRED: Understanding of the UK media landscape, including OTT and traditional broadcast advertising
- Familiarity with digital advertising and marketing analytics
- Experience applying statistical approaches such as regression and classification, as well as designing and analysing A/B and other controlled experiments
- Awareness of modern data architecture methodologies including Data Mesh and governance principles
- Hands-on experience with data visualisation platforms like Tableau, Looker, AWS QuickSight, and ThoughtSpot
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