Lead I - Data Engineering

5 - 7 Years
1 Opening
Trivandrum

Role Proficiency:

This role requires proficiency in data pipeline development including coding and testing data pipelines for ingesting wrangling transforming and joining data from various sources. Must be skilled in ETL tools such as Informatica Glue Databricks and DataProc with coding expertise in Python PySpark and SQL. Works independently and has a deep understanding of data warehousing solutions including Snowflake BigQuery Lakehouse and Delta Lake. Capable of calculating costs and understanding performance issues related to data solutions.

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Knowledge Management:

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Knowledge Examples

Additional Comments:

UST is seeking a highly skilled and motivated Lead Data Engineer to join our Telecommunications vertical, leading impactful data engineering initiatives for US-based Telco clients. The ideal candidate will have 6–8 years of experience in designing and developing scalable data pipelines using Snowflake, Azure Data Factory, Azure Databricks. Proficiency in Python, PySpark, and advanced SQL is essential, with a strong focus on query optimization, performance tuning, and cost-effective architecture. A solid understanding of data integration, real-time and batch processing, and metadata management is required, along with experience in building robust ETL/ELT workflows. Candidates should demonstrate a strong commitment to data quality, validation, and consistency, with working knowledge of data governance, RBAC, encryption, and compliance frameworks considered a plus. Familiarity with Power BI or similar BI tools is also advantageous, enabling effective data visualization and storytelling. The role demands the ability to work in a dynamic, fast-paced environment, collaborating closely with stakeholders and cross-functional teams while also being capable of working independently. Strong communication skills and the ability to coordinate across multiple teams and stakeholders are critical for success. In addition to technical expertise, the candidate should bring experience in solution design and architecture planning, contributing to scalable and future-ready data platforms. A proactive mindset, eagerness to learn, and adaptability to the rapidly evolving data engineering landscape—including AI integration into data workflows—are highly valued. This is a leadership role that involves mentoring junior engineers, fostering innovation, and driving continuous improvement in data engineering practices.

Azure Databricks,Snowflake,python,Data Engineering