Data Engineer

Key Responsibilities

Technical & 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.

● 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

● 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.

Client & Stakeholder Engagement

● Translate business requirements into robust technical solutions and roadmaps.

● Support pre-sales, solutioning, and client onboarding with technical leadership and estimation.

● Clearly communicate technical decisions, risks, and trade-offs to both technical and

non-technical stakeholders.

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

● 5+ years of experience in data engineering

● 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.

● Strong 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.