Senior Data Engineer

Overview

Senior Data Engineer

data engineering, analytics, business intelligence, and technical leadership

Responsibilities

• Design and develop

  enterprise-scale data pipelines and ETL/ELT solutions

  using

  Azure Data Factory, Azure Databricks, and Microsoft Fabric

  .
• Build scalable

  lakehouse and data warehouse solutions

  using

  ADLS, OneLake, Delta Lake, Synapse

  , and related technologies.
• Develop high-performance data processing solutions using

  SQL, Python, and PySpark

  .
• Design data models, dimensional schemas, analytical datasets, and semantic models for enterprise reporting and analytics.
• Build and optimize

  batch and near-real-time data pipelines

  , including API, event-driven, and streaming integrations where required.
• Establish robust practices for

  data quality, validation, reconciliation, governance, metadata, lineage, security, and compliance

  .
• Implement

  Git-based development, CI/CD, automated deployments, monitoring, and operational support

  for data solutions.
• Analyze complex datasets, define KPIs, and deliver actionable insights through

  Power BI and other BI platforms

  .
• Partner with business stakeholders to translate requirements into scalable data and analytics solutions.
• Support

  AI/ML and Generative AI initiatives

  by developing trusted, governed, and AI-ready data foundations.
• Lead data modernization and cloud transformation initiatives, including migration from legacy platforms to

  Azure/Fabric

  .
• Troubleshoot and optimize data pipelines, queries, Spark workloads, storage, and cloud costs.
• Provide technical guidance and mentorship to data engineers and analysts while driving engineering best practices.

Required Qualifications

• 8–10 years of experience

  in data engineering, analytics, BI, or related data disciplines.
• Strong hands-on experience with

  Azure Data Factory, Azure Databricks, and/or Microsoft Fabric

  .
• Strong knowledge of

  Azure Data Lake, OneLake, Delta Lake, lakehouse, and data warehouse architectures

  .
• Advanced

  SQL

  skills, including query optimization, partitioning, indexing, and performance tuning.
• Strong programming experience with

  Python and PySpark

  ; Scala is a plus.
• Strong understanding of

  data modeling, dimensional modeling, ETL/ELT, orchestration, and data architecture

  .
• Experience with

  Power BI or equivalent BI platforms

  and the ability to translate business requirements into analytical solutions.
• Experience with

  Git, Azure DevOps, CI/CD

  , and production data pipeline practices.
• Understanding of

  data governance, quality, security, metadata, lineage, and compliance

  .
• Experience with

  cloud data platforms and distributed processing technologies

  such as Databricks, Spark, Snowflake, Synapse, Kafka, or equivalent.
• Strong communication, stakeholder management, problem-solving, and technical leadership skills.

Preferred Qualifications

• Experience with

  Microsoft Fabric, OneLake, Fabric Data Factory, and Power BI

  .
• Exposure to

  real-time data processing, Event Hubs, Service Bus, APIs, or event-driven architectures

  .
• Experience with

  Terraform, Bicep, or other Infrastructure-as-Code technologies

  .
• Experience supporting

  AI/ML, Generative AI, or advanced analytics

  initiatives.
• Experience with enterprise data governance, cataloging, lineage, and master data management.
• Relevant Azure, Fabric, Databricks, Snowflake, or other cloud data certifications.
• Experience working in

  Agile/Scrum and global delivery environments

  .

What You'll Bring

• A strong engineering mindset focused on

  scalability, reliability, performance, and quality

  .
• Ability to move between

  technical implementation, data analysis, and business problem-solving

  .
• Strong ownership of data solutions from

  requirements and architecture through development, deployment, and production support

  .
• Curiosity to adopt modern

  cloud, data, analytics, and AI technologies

  .
• Ability to mentor others and influence technical decisions across teams.

Why Join Us?

• Lead modern

  Azure and Microsoft Fabric data transformation

  initiatives.
• Work across

  Data Engineering, Analytics, BI, and AI

  .
• Solve complex enterprise data challenges at scale.
• Collaborate with architects, engineers, analysts, data scientists, and business leaders.
• Build solutions that directly influence

  business decisions and outcomes

  .
• Grow your expertise through continuous learning, certifications, and exposure to modern data technologies.

Ready to build the future of data? Join our Data & Analytics team and help organizations turn data into trusted insights and intelligent business outcomes.

📩 Apply now.