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Tier-1 employer, popular Data Engineer title, metro location, and mid-level experience amplify competition.
Core data engineering skills transfer across industries, reducing sensitivity to sector-specific background.
Requires specific technical skills (ETL, Spark, data modelling) but no explicit years, so moderately strict.
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Own the development and execution of data integration (ETL) and data management practices ensuring unified and accurate data views.
Implement and maintain data processing frameworks and infrastructure, including database design, big data technologies, and data storage solutions.
Ensure data quality, security, governance, and compliance along with producing technical documentation and supporting CI/CD pipelines for data systems.
Proficient skills in data integration, ETL, data analysis, data modelling, data quality management, and programming (Python, R, SQL).
Foundational knowledge of data processing frameworks like Apache Hadoop and Apache Spark.
Experience in data management, database design, data security, data governance, and compliance.
Work Experience Required: Not explicitly mentioned in the JD.
Experience operating with end-to-end data lifecycle management including architecture, governance, and compliance in an enterprise environment.
Comfortable working across both traditional databases and big data technologies to design, implement, and maintain data storage and processing solutions.
Able to produce and maintain technical documentation and support automated development pipelines (CI/CD) for data systems to ensure reliability and scalability.