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Azure Data DevOps Engineer

Remote · Pakistan Full-time

At DIGITALL we don't just deliver technology, we deliver the future! We are explorers, knowledge-hunters, tech geeks, problem solvers and game changers who want to inspire and be inspired. Our DIGITALL people are always one step forward: working with top-notch technologies, creating innovations ahead of the market trends, sharing the passion for discovering better ways. As a human-centric organization, our teams are built on mutual respect and open communication, allowing everyone to be authentic, express ideas and unleash their potential. We are proud of our DIGITALL bright minds and never stop developing their skills to keep pushing boundaries together and do what we love. DIGITALL operates globally with a team of 1000 experts in 16 locations across 8 countries.

This is your job:

  • Cloud Platform & Architecture: Design, build, and support hybrid cloud and on-premises data solutions with a strong focus on Azure services, including data, identity, network, security, and analytics services.
  • Data Lakehouse Implementation: Practical design, administration, and execution using Databricks and Unity Catalog, managing notebooks, workspace configuration, workload isolation, and cost optimization. Work extensively with open storage formats such as Delta, Iceberg, and UniForm.
  • Data Modeling: Design, review, and maintain data models across Bronze, Silver, and Gold layers, including dimensional models for the serving layer. Guide and advise domain teams on grain, conformance, performance, and reusability.
  • ETL/ELT Pipeline Development: Expertise in designing, implementing, and optimizing data ingestion, transformation, and orchestration processes utilizing Azure Data Factory, Databricks, and dbt.
  • Data Integration & Virtualization: Handle API integrations, event-driven and batch patterns, message queues, as well as query federation and semantic layer technologies (e.g., Dremio).
  • Database & Infrastructure Operations: Work with relational databases (preferably PostgreSQL) managing structured, semi-structured, and unstructured data. Manage platform operations, including monitoring, logging, alerting, performance tuning, capacity planning, runbooks, and Azure VM management on Linux or Windows.
  • DevOps & Security: Apply CI/CD practices using Azure DevOps or GitHub Actions for automated build, test, and deployment, source control, artifact management, secrets management, and environment promotion. Ensure data governance, access control, data quality, lineage, and compliance.

Your qualifications:

  • Cloud & Lakehouse: Strong understanding of Azure cloud services, Databricks, Unity Catalog, and open table formats (Delta, Iceberg, UniForm).
  • Data Engineering & Modeling: Proven track record in data modeling across Bronze/Silver/Gold layers, dimensional modeling, and building ETL/ELT pipelines using Azure Data Factory, Databricks, and dbt.
  • Programming & Databases: Proficiency in Python and SQL (Scala or Java is a plus). Hands-on experience with PostgreSQL and diverse data types (structured, semi-structured, unstructured).
  • DevOps & Operations: Hands-on experience with Azure DevOps or GitHub Actions, secrets management, CI/CD, as well as platform operations (Azure VMs on Windows/Linux, monitoring, performance tuning).
  • Integration & BI Awareness: Knowledge of API/event-driven integrations, query federation tools (e.g., Dremio), BI concepts/tools (Power BI, Tableau), and Microsoft Fabric (OneLake, Lakehouse/Warehouse items, Power BI semantic layer).
  • Governance: Solid knowledge of data governance principles, data quality management, metadata, and access control/lineage.
  • Strong communication skills in English (written and oral).
  • Ability to effectively apply creative and practical problem-solving skills on a regular basis.
  • Certification in ITIL V3/V4 Foundation or SAFe v6 is a plus.

Organizational information:

  • All applications will be treated in strict confidentiality
  • Please note that only shortlisted candidates will be invited to an interview

Originally posted on

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