Are you passionate about building scalable, high-impact data solutions that drive critical business insights? We are seeking an experienced and forward-thinking Lead Data Engineer to join our dynamic team.
In this pivotal role, you will be at the forefront of designing and constructing our next-generation data architecture. You will tackle complex challenges in data ingestion, transformation, and quality, directly shaping our ability to make data-driven decisions. If you thrive on building robust systems from the ground up and want to see your work make a tangible difference, this is the opportunity for you.
Key Responsibilities
Design, develop, and maintain robust ETL/ELT pipelines to ingest, transform, and deliver data from diverse sources.
Contribute to the design of scalable data architectures, including data lakes, data warehouses, and lakehouse patterns.
Implement data quality checks, validation frameworks, and monitoring solutions to ensure data accuracy, completeness, and lineage compliance.
Build and optimize data solutions on cloud platforms leveraging services such as Spark, Kafka, Databricks.
Profile and tune SQL queries, Spark jobs, and pipeline workflows for efficiency and cost effectiveness.
Experience and Education:
Must to have 8-10 years of experience in Data Engineering
proficiency in Python, strong SQL skills
Hands on experience with Apache Spark, Hadoop, or equivalent distributed computing frameworks
Experience with relational databases and NoSQL systems
Knowledge on Machine Learning, AI would be added advantage
Bachelor’s degree/University degree or equivalent experience
This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.
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Job details are sourced from the employer's original posting.
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