Data Engineer
4 days ago
Nationality:
Any Nationality
Vacancy:
1 Vacancy
Job Description
Design and implement pipelines to ingest large volumes of data from diverse sources, like databases, APIs, and S3 buckets, into the data lake.
Work with various data formats, including Parquet, CSV, and JSON, ensuring compatibility and efficient processing.
Build, maintain and optimize ETL pipelines using Python (PySpark) & SQL.
Design, build, and maintain intermediate and business-layer tables for KPIs.
Automate data extraction, transformation, and loading processes using AWS tools such as AWS Glue and Athena.
Validate the accuracy and consistency of data being transformed and ingested into the business layer.
Implement data validation checks to identify and resolve discrepancies in raw or processed data.
Ensure data models and tables align with business needs for reporting and visualization tools like Power BI, Tableau, or Looker Studio.
Optimize queries and table structures to improve performance for large datasets in Amazon Redshift or Athena.
Ensure efficient usage of AWS resources to minimize costs while maintaining performance.
Desired Candidate Profile
Bachelor's degree in Computer Science, Data Science, or related field.
At least 5+ years of experience as a Data Engineer or similar role & hands-on experience in working with raw data transformation.
Proficiency in PostgreSQL, SQL, Advanced SQL, and ability to write complex queries for data aggregation and transformation.
Experience with AWS services like S3, Glue, Athena, and Redshift.
Proven experience with SQL and database management systems.
Strong understanding of data warehousing concepts and dimensional modeling.
Ability to translate business requirements into efficient data models and tables.
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