Senior / Lead Data Engineer

We are seeking a motivated Data Engineer with experience to design, develop, and maintain scalable data solutions on the Microsoft Azure platform. You will collaborate with cross-functional teams to enable data-driven decision-making using Azure Synapse Analytics, Data Factory, SQL, Python, and data analysis techniques. This role offers opportunities to grow your expertise in cloud data engineering while contributing to impactful projects.

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Key Responsibilities

• Data Pipeline Development: Build, deploy, and maintain efficient ETL/ELT pipelines using Azure Data Factory and Azure Synapse Analytics.
• For Data Engineers, Databricks and Fabric should must have skills, with Synapse being a good-to-have addition.
• We are only looking for senior candidates with over 6 yrs of relevant exp with ample client facing exp.
• Finance/Insurance experience is also a must.
• Data Modeling & Warehousing: Design and optimize data models, warehouses, and lakes for structured/unstructured data.
• SQL & Query Optimization: Write complex SQL queries, optimize performance, and manage databases.
• Python Automation: Develop scripts for data processing, automation, and integration using Python (Pandas, NumPy).
• Collaboration: Partner with data analysts/scientists to ensure data accessibility and quality for analytics/ML projects.
• Data Analysis: Perform exploratory data analysis (EDA) to uncover trends, anomalies, and actionable insights.
• Troubleshooting: Resolve data pipeline issues, ensuring reliability and compliance with governance standards.
• Documentation: Maintain clear technical documentation for architectures, processes, and workflows.

Continuous Learning: Stay updated on Azure advancements (e.g., Databricks, Purview) and industry best practices.

Qualifications:

• Education: Bachelors degree in Computer Science, Information Technology, Data Science, or a related field.
• Experience in data engineering, with hands-on exposure to Azure Synapse, Data Factory, SQL, and Python.
• Technical Skills:
• Proficiency in SQL (joins, CTEs, optimization) and Python for data tasks.
• Experience with Azure data services (Synapse, Data Factory, Storage).
• Basic understanding of ETL/ELT processes and data warehousing.
• Familiarity with Git for version control.
• Analytical Skills: Ability to analyze datasets, identify patterns, and communicate insights.

Soft Skills: Strong problem-solving, teamwork, and communication abilities