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