Position : -Snowflake Data Architect / Lead Data Engineer
Experience : 7 - 12 Years
Role : Individual Contributor + Project Lead
Qualifications: - Bachelor's or Master's degree in Computer Science, Engineering,
or a related field.

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).
● Solid hands-on experience with AWS data services — S3, Glue, EMR, Redshift,
DMS, Lambda, Step Functions, IAM, KMS.
● Proven delivery of at le

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