Snowflake Data Architect / Lead Data Engineer

Talent Corner Hr Services; Pune District; On-site; INR 3,500,000 - 5,500,000; Full time

Job summary

Talent Corner Hr Services seeks a Snowflake Data Architect / Lead Data Engineer in Pune to own end-to-end design, build, and delivery of enterprise data platforms — lakehouse architectures, cloud data warehouses, and analytics solutions for regulated industries. You will own the solution architecture and guide a team of engineers across delivery phases.

This role requires deep Snowflake and AWS experience, strong SQL and Python, data modeling, and governance.

Qualifications

• 7–10 years in data engineering / data architecture roles.
• Snowflake experience: 4+ years on Enterprise or Business Critical edition.
• Strong hands-on with AWS data services (S3, Glue, EMR, Redshift, DMS, Lambda).
• Proven delivery of large-scale data platform implementations (50+ users, TB-scale).

Responsibilities

• Lead end-to-end design, build, and delivery of enterprise data platforms (lakehouse and data warehouse) on AWS with Snowflake at the core.
• Mentor and guide a team of data engineers across delivery phases.
• Engage with clients and senior leadership; produce architecture documents and cost estimates.

Skills

Snowflake

AWS

Data Modeling

ETL/ELT Orchestration

Data Governance

Stakeholder Communication

Leadership

Tools

dbt

Airflow

Snowflake

Job description

Snowflake Data Architect / Lead Data Engineer

Experience: 710 Years | Role: Individual Contributor + Project Lead

What You'll Do

Lead end-to-end design, build, and delivery of enterprise data platforms — lakehouse architectures, cloud data warehouses, and analytics solutions for regulated industries (banking/financial services preferred). You'll own the solution architecture, guide a team of engineers, and be the technical authority on client engagements.

Key Responsibilities

• Architect and deliver enterprise lakehouse and data warehouse solutions on AWS (S3, Glue, EMR, Redshift) with Snowflake as the core analytical engine.
• Design multi-zone data lake architectures (Bronze / Silver / Gold) using open table formats (Delta Lake, Apache Iceberg) with ACID compliance and schema evolution.
• Build and optimise data pipelines — batch, CDC, and real-time streaming — using tools like AWS DMS, Glue Spark, MSK (Kafka), dbt, and Step Functions/Airflow.
• Define data models: Data Vault 2.0 for integration layers, dimensional star/snowflake schemas for consumption, and semantic layers for enterprise BI.
• Implement data governance frameworks — cataloguing, lineage, data quality (Great Expectations or equivalent), MDM, and BCBS 239 / regulatory compliance controls.
• Lead solution design workshops, produce architecture documents, and present to C-level and steering committees.
• Mentor and technically guide a team of 4–6 data engineers across delivery phases.
• Manage stakeholder expectations, delivery timelines, and quality gates on engagements sized at 6–12+ months.

Must-Have

• 7–10 years in data engineering / data architecture roles, with at least 4 years on Snowflake (Enterprise or Business Critical edition).
• Strong hands‑on experience with AWS data services — S3, Glue, EMR, Redshift, DMS, Lambda, Step Functions, IAM, KMS.
• Proven delivery of at least 2 large‑scale data platform implementations (50+ users, 10+ source integrations, TB-scale).
• Deep expertise in SQL, Python/PySpark, and data modelling (Data Vault, star schema, bi‑temporal).
• Experience with ETL/ELT orchestration tools — dbt, Airflow (MWAA), or equivalent.
• Working knowledge of data governance, data quality frameworks, and metadata management.
• Ability to produce solution architecture documents, cost estimates, and technical proposals.
• Excellent communication — comfortable leading client‑facing discussions and presenting to senior leadership.

Good to Have

• Experience in banking, financial services, or other regulated industries (RBI/RMA compliance, PCI DSS, ISO 27001).
• Exposure to AI/ML platforms — SageMaker, MLOps, Feature Stores, or GenAI (Bedrock/RAG).
• Snowflake certifications (SnowPro Advanced: Architect or Data Engineer).
• AWS Solutions Architect or Data Analytics Specialty certification.
• Experience with Oracle Analytics Cloud, Power BI, or Tableau for enterprise BI delivery.
• Familiarity with DevSecOps, CI/CD for data pipelines, and infrastructure‑as‑code (Terraform/CloudFormation).
• Prior experience with historical data migration and source‑to‑target reconciliation at scale.

Why This Role

Work on high‑impact, greenfield enterprise data platforms for banking and financial services clients. Own the architecture, shape the solution, and lead delivery end‑to‑end.