Data Engineer

Job Purpose As a Data Engineer, you will bring deep technical expertise and act as a subject-matter expert within the team. You will be responsible for the technical configuration, development, integration, and operation of data platforms and products built on our core technology stack. You will work closely with Product Owners, Product Architects, and cross-functional teams to understand business needs and translate them into robust technical solutions aligned with engineering standards and roadmaps.

You will contribute hands-on by implementing new features, writing high-quality code, following agile methodologies, and supporting the team in delivering on time. You are expected to be a proactive team player - maintaining documentation, raising questions, offering support, and actively participating in team ceremonies. You will also help drive continuous improvement in engineering practices and contribute to delivering high-quality solutions across the full data lifecycle.

Technology Stack Must Have Strong proficiency in Python and SQL Experience with big data technologies , including MPP and streaming Hands-on experience with cloud platforms (AWS, Azure, or GCP) Experience with data and compute platforms such as Databricks, BigQuery, or Snowflake Experience with CI/CD tools and processes (Azure DevOps, Jenkins, Git) Familiarity with APIs for data ingestion and extraction Ability to understand high-level design and architecture documents and translate them into development tasks Nice to Have Experience with Microsoft data stack (Azure Data Factory, Azure Synapse, Databricks, Fabric, Power BI) Data modelling and data architecture experience ETL pipeline design and optimization Advanced expertise in PySpark Logging and monitoring using Azure / Databricks services Experience with Apache Kafka or similar streaming platforms Exposure to machine learning and AI technologies Key Responsibilities Coach and mentor data engineers in designing, developing, and delivering scalable, reliable, and high-performance data solutions Design, develop, and maintain scalable data pipelines and ETL processes Monitor and optimize data infrastructure performance, resolving bottlenecks and issues Drive technical excellence through code reviews, design reviews, testing, and deployment practices Act as an individual contributor (~60%), engineering software solutions alongside the team Ensure adherence to coding standards, best practices, and architectural guidelines Oversee implementation of technical architecture and resolve complex technical challenges Ensure DevSecOps practices are embedded in daily team operations Guide development approaches and manage technical debt Hire, onboard, mentor, and develop engineering talent, fostering a culture of collaboration and continuous improvement Lead technical discussions with cross-functional teams when required Represent the data engineering domain in broader technical and architectural discussions Design and improve processes to enhance delivery efficiency and solution quality Collaborate with Engineering Manager, Product Owner, Business Analyst, and Scrum Master to align on sprint goals, timelines, and resources Requirements 4–7 years of experience in Data Engineering Strong hands-on experience with data integration, ETL processes, and data warehousing In-depth knowledge of the mandatory technology stack Strong understanding of software engineering principles, coding standards, and modern architectures Familiarity with data governance and compliance standards Experience delivering end-to-end DataOps / Data Engineering projects within a team Proven ability to guide and mentor engineers with varying experience levels Experience working across diverse projects, technologies, and systems Strong problem-solving and decision-making skills Ability to work independently and take initiative Excellent collaboration and communication skills A pragmatic mindset and strong team orientation