Senior Data Engineer

Key Responsibilities

Data Engineering & Pipeline Development

• Design, build, and maintain robust ETL/ELT pipelines to ingest, transform, and deliver data for reporting use cases
• Develop curated data layers (e.g., bronze/silver/gold) optimized for BI consumption
• Ensure high data quality through validation, monitoring, and automated checks

Reporting Infrastructure Enablement

• Build and optimize data models to support scalable reporting
• Partner with analytics teams to translate business requirements into performant data structures
• Enable self-service reporting by creating well-documented, reusable datasets

Platform & Performance Optimization

• Improve performance of data pipelines and queries for large-scale datasets
• Implement efficient partitioning, indexing, and query optimization strategies
• Support cloud-based environments (e.g., Azure, AWS, or GCP)

Data Governance & Reliability

• Establish standards for data lineage, documentation, and metadata management
• Ensure adherence to data governance, security, and compliance practices
• Monitor pipelines and troubleshoot issues proactively

Required Qualifications

• 4–8+ years of experience in data engineering or data platform development
• Robust proficiency in SQL, Python, and AWS
• Experience building pipelines with tools such as:
  • Azure Data Factory, Databricks, Airflow, or equivalent
• Experience with data warehousing solutions (e.g., Snowflake, Synapse, Redshift, BigQuery)
• Robust understanding of data modeling concepts (star schema, dimensional modeling)
• Experience supporting BI/reporting tools (e.g., Power BI, Tableau)

Preferred Qualifications

• Experience building reporting infrastructure from scratch or during organizational expansion
• Familiarity with data contracts and data product thinking
• Exposure to DevOps and CI/CD pipelines for data (Git, automated deployments)
• Experience working in distributed/global teams