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Popular mid-level data engineer role at a well-known services firm increases applicant density.
Data engineering skills are broadly transferable across industries despite some domain mentions.
Moderate technical filters (Snowflake, Databricks, cloud) without explicit years requirement.
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Develop and implement data ingestion and ETL processes to load and transform data into data lakes/warehouses.
Design and optimize data storage and retrieval solutions ensuring data quality and integrity across pipelines.
Collaborate with data scientists and analysts to deliver relevant datasets; research and evaluate new data technologies for continuous improvement.
Bachelor's degree in Business Analytics, Computer Science, Statistics, or Master’s in Data Science.
Work Experience Required: Not explicitly mentioned in the JD.
Proficient in English (C2 level) and familiar with Agile methodology and cloud computing.
Office location-based role with night shift in India; essential certifications include Microsoft Azure Data Engineer Associate and Databricks Certified Associate Developer for Apache Spark (preferred).
Experienced data engineer skilled in building and maintaining large-scale ETL pipelines and data storage solutions.
Comfortable working in agile, fast-paced environments collaborating closely with data scientists and analysts.
Has relevant certifications and experience in cloud platforms (Azure) and data engineering tools like Apache Spark and Snowflake.