Senior Data Engineer
Skills
About the role
Experience: 8–10 years in Data Engineering and Data Analysis.
Informatica Expertise: Strong hands-on experience in Informatica PowerCenter/IDQ for ETL design, development, and optimization.
PySpark Development: Advanced skills in PySpark for large-scale data processing, transformation, and analytics.
Hadoop Ecosystem: Solid working knowledge of Hadoop technologies (HDFS, Hive, Sqoop, MapReduce).
Programming Skills: Proficiency in Python and Kafka for streaming and batch data pipelines.
Database & Modeling: Strong understanding of database concepts, data design, data modeling, and ETL workflows.
ETL Lifecycle: Experience in analyzing, designing, and coding ETL programs including data extraction, ingestion, quality checks, normalization, and loading.
Agile Delivery: Hands-on experience with Agile methodology and Jira for project delivery.
Client Interaction: Proven ability in client-facing roles with strong communication and leadership skills to coordinate across SDLC.
Senior Data Engineer (Informatica & PySpark)
Preferred Skills:
Exposure to AWS data components and analytics.
Familiarity with machine learning models and AI concepts.
Experience with data modeling tools such as Erwin.
Qualifications
Master’s or Bachelor’s degree in Computer Science or related field.
Strong problem-solving skills and ability to work in cross-functional teams.
Questions about this role
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