JOB REQUIREMENTS

English Level: Professional proficiency (written and spoken)

Domain: Life Insurance domain is required.

Technical Leadership & Architecture

• Own and define enterprise data architecture leveraging Azure Data Platform, Databricks, and Snowflake.

• Establish and enforce engineering standards, best practices, and design patterns for data ingestion, transformation, and analytics.

• Lead architectural reviews covering scalability, performance, security, governance, and cost optimization.

• Design and guide lakehouse architectures using Azure Data Lake Storage (ADLS), Databricks, and Snowflake.

• Make strategic technology decisions across Azure-native, Databricks, and Snowflake ecosystems.

Delivery & Execution

• Lead large-scale data migrations from on-premise or legacy platforms to Azure, Databricks, and Snowflake.

• Oversee development of robust ETL/ELT pipelines using tools such as Azure Data Factory, Databricks (Spark), SQL, and Python.

• Ensure data quality, reliability, observability, and performance across all pipelines.

• Guide teams through iterative delivery while managing technical risks and changing requirements.

Team Enablement & Mentorship

• Lead and mentor data engineers through code reviews, design sessions, and technical coaching.

• Drive technical excellence and raise the maturity of data engineering practices across teams.

• Support onboarding and skill development for engineers working with Azure, Databricks, and Snowflake.

Documentation & Governance

• Ensure production-grade technical documentation, including architecture diagrams, data models, and operational runbooks.

• Define governance standards for data security, access control, CI/CD, and version control.

Must-Have Qualifications

• 7+ years of experience in data engineering, with 3+ years in a Lead or Tech Lead role.

• Strong expertise in Azure Data Platform, including:

○ Azure Data Lake Storage (ADLS Gen2)

○ Azure Data Factory

○ Azure Synapse Analytics (knowledge)

• Deep hands-on experience with Databricks (Apache Spark, Delta Lake, notebooks, workflows).

• Strong experience designing and operating Snowflake data warehouses.

• Advanced skills in SQL and Python for large-scale data processing.

• Proven experience leading complex data migrations and modernization initiatives.

• Strong understanding of data modeling, performance tuning, and cost optimization.

• Ability to manage multiple workstreams and shifting priorities.

• Excellent English communication skills for client leadership, workshops, and documentation.

Preferred Qualifications

• Experience with CI/CD for data platforms (Azure DevOps, GitHub Actions).

• Knowledge of data governance, security, and compliance (RBAC, data masking, encryption).

• Familiarity with streaming architectures (Azure Event Hubs, Kafka).

• Experience with multi-cloud or hybrid data architectures.

• Relevant certifications (preferred):

○ Azure Data Engineer Associate / Expert

○ Databricks Data Engineer Professional

○ Snowflake SnowPro Advanced