Senior Data Engineer

ETL/ELT Development:

• Architect, build, and maintain scalable ETL and ELT pipelines using Databricks, Snowflake, Azure Data Factory, or similar orchestration frameworks.
• Drive reliable, high-volume data ingestion from heterogeneous sources into centralized storage systems (DWH/data lakes).
• Define and enforce engineering best practices, code reviews, and pipeline standards across the team.

Data Modelling & Warehousing:

• Design and own relational and dimensional data schemas tailored to complex business use cases in data lakes and modern warehouses (e.g., Snowflake, Databricks Lakehouse, Redshift, Postgres).
• Develop and optimize data models for large-scale analytics, reporting, and self-service BI consumption.

Database Engineering:

• Write and optimize complex SQL queries, stored procedures, and transformations to clean, aggregate, and prepare data for analytics workloads.
• Lead performance tuning, query optimization, and cost optimization across Snowflake / Databricks environments.

BI & Visualization Support:

• Partner with BI teams to enable report and dashboard development in Tableau or Power BI.
• Collaborate with analysts and business users to translate reporting needs into robust data products and self-service BI enablement.

Performance & Data Quality:

• Monitor, troubleshoot, and continuously improve data pipelines and warehouse jobs to ensure timely, accurate, and reliable data availability.
• Implement and govern data quality frameworks, validations, and observability practices to ensure trustworthiness of data outputs.

Leadership & Collaboration:

• Mentor junior data engineers and contribute to technical roadmaps and architectural decisions.
• Partner cross-functionally with product, analytics, and engineering teams to deliver end-to-end data solutions.