Back
Tier-1 brand, popular Data Engineer title, metro location, mid-level range, and broad platform requirements raise competition.
Core data engineering skills are industry-agnostic, so background fit is low sensitivity.
Explicit 2–5 years plus multiple platform requirements create moderately strict shortlisting filters.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop, optimize, and maintain data pipelines and structures ensuring data quality and efficient processing for analytics and reporting.
Manage data storage solutions across on-premise (minIO, Teradata) and cloud platforms (AWS S3, Redshift), including API development and platform management (Kubernetes, Databricks).
Collaborate with technology partners to optimize data sourcing, adhere to data governance/compliance standards, and support ETL processes and model deployment.
Bachelor's Degree preferred; relevant combination of coursework and professional experience may be considered.
2-5 years of relevant work experience in data engineering or related roles.
Ability to work night and weekend shifts with a variable schedule as necessary.
Experience with data storage and processing platforms such as Kubernetes, Teradata, Databricks, AWS S3, Redshift, and knowledge of data governance.
Experienced in designing and maintaining complex, large-scale data pipelines with strong data quality focus.
Skilled in managing both cloud and on-premise data storage solutions and handling data migrations and transformations.
Capable of collaborating cross-functionally to optimize data sourcing and processing rules while adhering to regulatory compliance.