Senior Data Engineer

Job Title: Senior Data Engineer

Location:

Key Responsibilities

• Design, build, and maintain

  scalable, reliable data pipelines

  using Azure data services to support analytics, data science, and business reporting use cases.
• Develop and manage

  data ingestion, transformation, and integration workflows

  using

  Azure Data Factory, Azure Databricks, and Azure Synapse Analytics

  .
• Implement and optimize

  Medallion architecture (BronzeSilver–Gold)

  to ensure structured, governed, and efficient data processing.
• Design and maintain

  data models and data warehouses

  that enable performant querying and downstream analytics consumption.
• Ensure

  data quality, consistency, security, and governance

  across pipelines by implementing validation checks, monitoring, and access controls.
• Work closely with data science, BI, and business teams to understand data requirements and translate them into robust engineering solutions.
• Optimize pipeline performance, cost, and reliability through tuning, partitioning, and efficient resource usage.
• Troubleshoot data issues, perform root-cause analysis, and proactively address pipeline failures or bottlenecks.
• Document data flows, transformations, and architecture to support maintainability and knowledge transfer.
• Communicate progress, risks, and dependencies clearly to stakeholders, and support delivery planning and execution.

Required Qualifications

• 4+ years of experience

  as a Data Engineer, with

  at least 3 years of hands-on experience

  working with

  Azure data services

  .
• Strong understanding of

  data engineering fundamentals

  , including data modelling, ETL/ELT patterns, and data warehousing concepts.
• Proven expertise in:

• Azure Data Factory

• Azure Databricks

• Azure Synapse Analytics

• Azure Data Lake Storage

• Unity Catalog

• Strong proficiency in

  SQL

  and experience working with

  NoSQL databases

  such as

  Azure Cosmos DB

  and

  Azure Table Storage

  .
• Proficiency in

  Python

  for data processing, automation, and orchestration.
• Experience implementing

  data quality checks, governance standards, and security best practices

  .
• Ability to design

  scalable and performant data architectures

  that can support large-scale, multi-source data workloads.
• Strong communication skills with experience in

  managing stakeholder expectations

  and explaining technical concepts to non-technical audiences.
• Prior experience

  leading or mentoring junior team members

  and contributing to team delivery and planning.

Preferred Qualifications

• Experience working in

  cloud-native, notebook-based environments

  (e.g., Databricks notebooks).
• Familiarity with

  CI/CD practices

  for data pipelines and infrastructure.
• Exposure to

  cost optimization

  and performance tuning in Azure-based data platforms.
• Experience working in

  large enterprise or multi-region data environments

  .
• Understanding of downstream analytics and reporting needs (BI, data science, forecasting) to better align engineering solutions.