Experience with data platforms and tools:
Snowflake, DBT, Databricks, Azure (ADF & Fabric), and GCP BigQuery
.
Strong understanding of database optimization techniques:
partitioning, indexes, query performance tuning
, etc.
Proficient in coding with
Python, PySpark
, and
SQL
for data extraction, transformation, and analysis.
Strong SQL expertise is a must
Experience in
automating and testing data workflows
, preferably using
Azure ADF
.
Familiarity with analytical techniques including
data modeling, data transformation
, and
algorithmic development
.

Role & responsibilities

End-to-End Pipeline Development -
Design, build, and test complete data pipelines for ingestion, integration, and curation.
Workflow Automation & Data Quality -
Automate data workflows and testing to boost efficiency and ensure data integrity.
Pipeline Optimization -
Continuously enhance pipeline performance to meet evolving business demands.
Scalable Cloud Data Platform
- Build and maintain a scalable, high-availability cloud-based data platform.
Technical Debt Management
- Identify and reduce technical debt for a clean and efficient codebase.
Reusable Frameworks -
Develop modular components and frameworks to accelerate data engineering tasks.
Stakeholder Collaboration

-
Partner with analysts and cross-functional teams to deliver data-driven solutions.
Documentation & Maintenance
- Document workflows and systems for clarity, consistency, and long-term support.

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