The ideal candidate must possess strong communication and collaboration skills, with the ability to design and build robust data architectures. They should demonstrate ownership in delivering scalable data solutions, working across technical and business teams to support analytics and BI requirements. The candidate should be proactive in identifying issues in data quality and have a strong sense of responsibility towards governance and compliance.
Role and Responsibilities:
------------------------------
Design, build, and maintain scalable and efficient data pipelines
for ingesting and transforming data from multiple sources.
Develop and manage
cloud-based data lakes optimized for analytics and business intelligence usage
.
Work closely with data science and BI teams to understand data requirements and ensure seamless integration of datasets.
Implement and maintain
data quality checks, data profiling, and monitoring mechanisms
.
Establish and
enforce
data governance policies
including data lineage, cataloging, and access control.
Optimize data processing workloads
for performance and cost-efficiency in cloud environments.
Collaborate across teams to understand evolving data needs and improve data infrastructure accordingly.
Technical and Functional Skills:
------------------------------------
BE or B.Tech graduate with 5+ years of experience in Data Engineering.
Proficient in SQL and Python for data manipulation and ETL development.
Experience with
ETL tools such as Alteryx, Tableau Prep, Apache Airflow
, or similar.
Strong hands-on experience with cloud platforms like
Azure (especially services like S3, BigQuery, Redshift, Glue, Dataflow, or equivalent), AWS, GCP.
Experience with
data lake architecture
and file formats like Parquet, Avro, or Delta Lake.
Working knowledge of data quality and observability tools
like Great Expectations or Monte Carlo
(Good to have).
Familiarity with metadata management, data cataloging, and governance frameworks.
Ability to design data models, understand business needs, and translate them into efficient data workflows.
* Experience with Tableau, Power BI, Looker for downstream BI integration and data integrity testing.
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