About the role :

As a Senior Data Engineer BI Analytics & DWH, you will lead the design and implementation of enterprise-grade business intelligence and data warehousing solutions that empower our organization to make data-driven decisions at scale.

You will leverage your deep expertise in Snowflake and/or Databricks, modern ETL/ELT frameworks, and cloud-native architectures to build scalable, high-performance data platforms.

This role demands a strategic thinker with strong technical leadership, hands-on engineering skills, and the ability to mentor junior engineers while collaborating with stakeholders at all levels.

What You'll Do :

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., 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.

On your first day, we'll expect you to have :

- Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field.

- 10+ years of hands-on experience in data engineering with deep ETL/ELT development and data modeling expertise.

- Strong hands-on experience with Snowflake or Databricks candidates with expertise in both will be strongly preferred.

- Advanced SQL skills with experience across database systems such as Snowflake, Databricks, SQL Server, Postgres, or Redshift.

- Solid experience with cloud-based services and data tools (e.g, AWS S3, Azure Data Factory, Databricks, Lambda functions).

- Strong understanding of data serialization formats like JSON, Parquet, and CSV.

- Proficiency in Python for scripting, automation, and data manipulation.

- Proven ability to design scalable data architectures and lead delivery of complex data initiatives.

Bonus :

- Hands-on exposure to visualization tools such as Power BI or Tableau for dashboard/report development.

We'd be super excited if you have :

- Snowflake or Databricks certifications.

- Azure SDK experience.

- Experience interacting with REST APIs and performing web scraping.

- Prior experience mentoring or leading small data engineering teams.