Key Responsibilities

- Architect and deliver enterprise Lakehouse and Data Warehouse solutions on AWS using S3, Glue, EMR, Redshift, and Snowflake.
- Design Bronze/Silver/Gold data lake architectures using Delta Lake and Apache Iceberg with ACID compliance and schema evolution.
- Build and optimize batch, CDC, and real-time data pipelines using AWS DMS, Glue Spark, MSK/Kafka, dbt, Step Functions, and Airflow.
- Design Data Vault 2.0, dimensional, star/snowflake, and semantic data models.
- Implement data governance, cataloguing, lineage, data quality, MDM, and regulatory compliance controls.
- Lead solution design workshops and prepare architecture documents, cost estimates, and technical proposals.
- Present solutions to clients, C-level stakeholders, and steering committees.
- Mentor and technically guide a team of 4 6 Data Engineers.
- Manage stakeholder expectations, delivery timelines, quality, and technical milestones for long-term engagements.

Must-Have Skills





- 7.5 12 years of experience in Data Engineering / Data Architecture, with 4+ years of Snowflake experience.
- Robust hands-on expertise in AWS: S3, Glue, EMR, Redshift, DMS, Lambda, Step Functions, IAM, and KMS.
- Experience delivering large-scale data platform implementations with multiple source integrations and TB-scale data.
- Strong expertise in SQL, Python/PySpark, and Data Modelling.
- Experience with Data Vault 2.0, Star Schema, and Bi-Temporal modelling.
- Hands-on experience with dbt, Airflow/MWAA, or equivalent orchestration tools.
- Knowledge of Data Governance, Data Quality, Metadata Management, and Lineage.
- Ability to create Solution Architecture Documents, Cost Estimates, and Technical Proposals.
- Excellent communication and client-facing presentation skills.

📌 Snowflake Data Architect / Lead Data Engineer – AWS | 7 – 12 Years | Pune (Maharashtra)
🏢 Seventh Contact Hiring Solutions
📍 Maharashtra