Purpose of the Position :

This role seeks a candidate who is passionate about building and optimizing cloud-based data platforms that support modern analytics initiatives. You will assist in implementing scalable Snowflake data pipelines, building efficient ingestion and transformation workflows, and supporting migration from legacy ETL systems to dbt-driven ELT architectures. The role contributes to improving data accessibility, performance, and consistency across the enterprise analytics environment.

Location : Chennai/Pune/Bangalore/Nagpur

Type of Employment :

Full-time

Key Result Areas and Activities :

1. DBT Architecture Strategy & Standardization :

- Define enterprise dbt architecture standards, layering conversions, naming frameworks, and modular transformation design approaches supporting large-scale modernization programs.

2. Code Conversion, Refinement and Optimization :

- Convert complex SSIS transformations into dbt staging/intermediate/mart models, review and validate tool-converted dbt transformations to ensure accuracy, maintainability, and alignment with enterprise modeling standards.

3. Legacy ETL Migration Enablement :

- Lead transformation strategies of migrating SSIS pipelines to dbt-based ELT frameworks while ensuring consistency, scalability, and maintainability.

4. Reusable Framework & Accelerator Development :

- Establish macro libraries and reusable template migration accelerators to improve delivery efficiency across multiple transformation streams.

5. Data Quality & Validation Strategy :

- Define reconciliation strategies/methodologies, parallel-run validation frameworks, and transformation testing standards supporting enterprise analytics reliability.

6. Performance Alignment with Snowflake Platform :

- Collaborate with Snowflake engineering teams to optimize execution strategy, clustering approaches, and warehouse utilization.

7. Governance, CI/CD & Delivery Oversight :

- Establish version control standards, CI/CD integration practices, and documentation frameworks supporting controlled migration execution.

8. Documentation and Lineage Support :

- Maintain transformation documentation, mapping logic, testing evidence, and lineage metadata to support governance and audit readiness.

9. Collaboration & Delivery Support :

- Work closely with Snowflake engineers, QA teams, and client stakeholders to resolve transformation discrepancies and ensure timely migration delivery.

Essential Skills :

- Strong experience designing enterprise-scale dbt transformation architecture.

- Hands-on experience leading legacy ETL modernization programs (SSIS to ELT).

- Experience developing reusable macros frameworks and modeling standards.

- Experience implementing incremental pipeline architecture at scale.

- Experience defining data validation and reconciliation frameworks.

- Strong expertise in dimensional modeling and analytical layer design.

- Hands-on experience optimizing Snowflake transformation workloads.

- Experience implementing CI/CD workflows for transformation deployments.

- Familiarity with version control systems (GIT/Azure DevOps).

Desirable Skills :

- Exposure to implementing dbt mesh architecture.

- Exposure to metadata-driven transformation frameworks.

- Experience integrating governance and lineage tooling.

- Familiarity with terraform-based infrastructure automation.

- Exposure to enterprise data platform modernization programs.

- Experience collaborating with platform engineer teams for workload optimization.

- Experience mentoring junior engineers in transformation programs.

Qualifications :

- Experience : 7+ years of experience in data engineering, ETL/ELT development, and hands-on dbt development.

- Education : Bachelors in computer science, Information Technology, or equivalent.

Qualities :

- Architecture-first thinking.

- Ability to work with cross-functionally dependent teams and stakeholder alignment.

- Migration risk anticipation capability.

- Delivery acceleration mindset.

- Validation strategy planning and defect triage prioritization.

- Detail-oriented with a focus on data accuracy and reliability.

- Attention to transformation accuracy.