About the role
structured by ORIAre 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.
What you will do
- 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.
What they are looking for
- 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
- Bachelor’s degree/University degree or equivalent experience
Nice to have
- Knowledge on Machine Learning, AI would be added advantage
Full posting text
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 Family Group:
Technology
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Job Family:
Applications Development
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Time Type:
Full time
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Most Relevant Skills
Please see the requirements listed above.
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Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.
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