Data Engineer (Snowflake + Azure Databricks + dbt/Matillion)

Ovii's Interpretation of the Role

We need a Data Engineer who can design, build, and operate high‑performance ELT pipelines on Snowflake and Azure Databricks. The candidate will own end‑to‑end data flows, ensure data quality, and collaborate with analysts and data scientists in a fast‑paced consulting environment.

Role Snapshot

• Design and implement scalable ELT pipelines
• Develop data models on Snowflake and Databricks
• Orchestrate workflows with Airflow, Azure Data Factory or similar
• Maintain CI/CD and Git‑based version control
• Collaborate with cross‑functional analytics teams
• Ensure data quality, governance and performance tuning

Must-Have Requirements

• Snowflake
• Azure Databricks
• dbt
• Matillion DPC
• SQL
• Python / PySpark
• Git
• CI/CD
• Delta Lake
• data engineering
• ELT pipeline development

Nice-to-Have Signals

• Client‑facing consulting experience
• AI/ML pipeline exposure
• MLflow basics
• Data quality tooling exposure
• Relevant certifications (SnowPro, Databricks, dbt)
• Airflow / Azure Data Factory / Databricks Workflows
• Cloud storage platforms (Azure Data Lake, AWS S3, GCS)
• Data modeling (Kimball/Dimensional) – preferred
• client‑facing consulting
• AI/ML data pipelines

Work Setup

• Location: Hyderabad, India
• Work mode: ONSITE
• Employment type: Full-Time

Not Specified in JD

• Visa sponsorship
• Salary range
• Remote eligibility
• Education requirement
• Certifications
• Relocation
• Notice period
• Travel
• Security clearance
• Coding test
• Portfolio
• GitHub
• Writing sample
• Cover letter

What You'll Likely Work On

• Design, configure and optimize ingestion, transformation, and orchestration workflows using Matillion DPC where needed
• Build and maintain ELT pipelines on Snowflake with dbt, applying best‑practice testing, documentation and version control
• Develop Spark‑based processing jobs on Azure Databricks, including notebooks, Delta Lake tables and lakehouse/medallion architectures
• Integrate data from relational databases, APIs, cloud storage and flat files into Snowflake and Databricks
• Schedule and monitor pipelines with Airflow, dbt Cloud, Azure Data Factory or Databricks Workflows
• Perform performance tuning in Snowflake and Databricks (clustering, materializations, partitioning, caching)
• Own pipeline lifecycle from design through production support, delivering client‑ready solutions
• Share knowledge via internal tech talks, documentation and collaborative code reviews

Good Fit If You Have

• Previous client‑facing or consulting experience
• Exposure to AI/ML feature stores or MLflow
• Relevant certifications (SnowPro, Databricks Certified Data Engineer, dbt Certified Developer)