Associate Data Engineer supporting privacy engineering controls and executing privacy impact assessments in a financial services company. Collaborating across business units to ensure alignment with privacy regulations.
About the role
- Data Engineer focusing on data pipeline development and analytics for a global tech company. Collaborating with teams to ensure data availability and quality standards.
Responsibilities
- Design, develop, and maintain data pipelines (batch and streaming) for ingestion, transformation, and delivery of data for analytics and application consumption.
- Build and evolve analytical modeling (bronze/silver/gold layers, data marts, star schemas, wide tables), ensuring consistency, documentation, and reusability.
- Implement data quality best practices (tests, validations, contracts, SLAs/SLOs, monitoring of freshness/completeness/accuracy) and manage incident resolution with root cause analysis (RCA).
- Define and maintain technical data governance: catalog, lineage, versioning, naming conventions, ownership, access policies, and audit trails.
- Optimize performance and cost of queries and pipelines (partitioning, clustering, incremental loads, materializations, job tuning).
- Support the full delivery lifecycle (discovery → development → validation → operations), aligning business requirements with technical needs and ensuring predictability.
- Collaborate with BI/Analytics teams to define metrics, dimensions, facts, and the semantic layer, ensuring traceability of key indicators.
- Enable and operationalize AI/ML use cases.
- Integrate sources and systems (APIs, databases, queues, events, files), ensuring security, idempotency, fault tolerance, and end-to-end traceability.
- Produce and maintain technical and functional documentation relevant for auditing, support, and knowledge transfer.
Requirements
- Proven experience as a Data Engineer focused on Analytics (building pipelines, modeling, and making data available for consumption).
- Strong command of SQL and solid experience with Python (or an equivalent language) for data engineering and automation.
- Experience with orchestration and workflow design (e.g., Airflow, Dagster, Prefect, or similar).
- Experience with data warehouses/lakehouses and analytical formats/architectures (e.g., BigQuery, Snowflake, Databricks, Spark; Parquet, Delta, Iceberg).
- Hands-on experience with ETL/ELT, incremental loads (CDC when applicable), partitioning, and performance/cost optimization.
- Knowledge of data quality and reliability best practices (data testing, observability, metrics, incident management, and RCA).
- Experience with version control (Git) and delivery practices (code review, branching patterns, basic CI).
- Strong verbal and written communication skills for interacting with technical teams and stakeholders, with the ability to translate requirements into clear deliverables.
Benefits
- Health and dental insurance;
- Meal and grocery allowance;
- Childcare assistance;
- Extended parental leave;
- Partnerships with gyms and health/wellness professionals via Wellhub (Gympass) TotalPass;
- Profit-sharing program;
- Life insurance;
- Continuous learning platform (CI&T University);
- Employee discount club;
- Free online platform dedicated to physical and mental health and wellbeing;
- Pregnancy and responsible parenting course;
- Partnerships with online course platforms;
- Language learning platform;
- And many more
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Data Engineer at CVS Health optimizing data pipelines and analytical models. Driving data - driven decisions with healthcare data for improved business outcomes.
Senior Data Engineer at CVS Health developing robust data pipelines for healthcare data. Collaborating with teams to provide actionable insights and integrate them with consumer touchpoints.
Senior Data Engineer supporting AI - enabled financial compliance initiative with data pipelines and ingestion processes. Collaborating with diverse teams in a mission - critical regulated environment.
Data Architect leading the definition and construction of cloud data architecture for Kyndryl. Participating in significant technological modernization initiatives, focusing on Google Cloud Platform.
Senior Data Engineer driving data intelligence requirements and scalable data solutions for a global consulting firm. Collaborating across functions to enhance Microsoft architecture and analytics capabilities.
Experienced AI Engineer designing and building production - grade agentic AI systems using generative AI and large language models. Collaborating with data engineers, data scientists in a tech - driven company.
Intermediate Data Engineer designing and building data pipelines for travel industry data management. Collaborating across teams to ensure reliable data for analytics and reporting.
Data Engineer managing and organizing datasets for AI models at Walaris, developing AI - driven autonomous systems for defense and security applications.
Data Engineer designing and maintaining data pipelines at Black Semiconductor. Collaborating with process, equipment, and IT teams to support manufacturing analytics and decision - making.