Data Engineer - ETL / PySpark

We are seeking a highly skilled Data Engineer who will be responsible for the technical execution and delivery of the data engineering roadmap.

The ideal candidate will have strong experience in cloud-based data architecture (especially Azure), data modeling, and data pipeline development.

Key Responsibilities :

• Translate business and analytics requirements into robust, scalable technical solutions aligned with the data roadmap.
• Oversee the technical assessment of new requests, supervise backlog grooming, and guide the development team to ensure delivery aligns with scope, time, and quality expectations.
• Design, build, and maintain efficient and secure data architecture leveraging Azure services and modern data engineering practices.
• Develop and manage scalable ETL / ELT processes using Azure Data Factory, Databricks, and other relevant tools.
• Implement and maintain best practices around data governance, data quality, metadata management, and lineage tracking.
• Work collaboratively in cross-functional agile teams.
• Participate in sprint planning, reviews, and retrospectives, ensuring adherence to DevOps and IaC principles.
• Mentor junior data engineers and contribute to improving team knowledge and technical Qualifications :
• Bachelors or Masters degree in Computer Science, Engineering, Information Systems, or a related field.
• 6+ years of experience in data engineering, data architecture, or related roles.
• Proven expertise in :
• Proven expertise in Azure Cloud Services particularly Azure Data Factory, Azure Databricks, Azure Data Lake, Azure Synapse.
• Experience in Big Data technologies, distributed data processing, and performance tuning.
• Experience in SQL, Python, PySpark for data transformations and processing.
• Strong foundation in data modeling, data warehousing, and data management principles.
• Experience with data governance tools and best practices.
• Knowledge of Terraform or other Infrastructure as Code (IaC) tools.
• Solid understanding of DevOps, CI / CD pipelines, version control, and automated testing frameworks.
• Familiarity with Agile / Scrum methodologies.
• Experience with BI platforms like Power BI, Tableau, or Looker.
• Understanding of machine learning pipelines and MLOps concepts.
• Familiarity with Kafka, Event Hubs, or other streaming platforms.
• Certifications such as Microsoft Certified : Azure Data Engineer Associate or Azure Solutions Architect Expert

ref : hirist.tech)