The Value Maximizer
Overview
We are seeking a skilled and motivated
Data Engineer with strong expertise in PySpark, SQL
to join our Data Engineering team. You will be responsible for designing, building, and maintaining scalable data pipelines and processing systems that support our business intelligence, analytics, and machine learning initiatives. Responsibilities
Develop and maintain scalable, robust data pipelines using Scala and big data technologies Work with large datasets from multiple sources to ingest, transform, and make data available for analytics and reporting Collaborate with Data Scientists, Analysts, and other engineers to understand data requirements and deliver efficient solutions Optimize ETL jobs for performance and cost Ensure data quality, governance, and consistency across all environments Monitor production jobs, troubleshoot issues, and ensure system reliability Implement best practices for data engineering, including code reviews, testing, and documentation Required Qualifications
Bachelor\'s or Master\'s degree in Computer Science, Engineering, or related field 6+ years of experience as a Data Engineer or in a similar role Strong skills in PySpark and SQL (experience with functional programming is a plus) Hands-on experience with big data tools like Apache Spark, Kafka, Hadoop, or Hive Proficiency in building ETL pipelines and working with structured and unstructured data Experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services Familiarity with version control systems (e.g., Git), CI/CD, and DevOps practices Solid understanding of data warehousing and data modeling concepts Preferred Qualifications
Knowledge of SQL and database systems such as Postgres, Redshift, or Snowflake Exposure to containerization technologies like Docker and orchestration tools like Airflow or Kubernetes
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We are seeking a skilled and motivated
Data Engineer with strong expertise in PySpark, SQL
to join our Data Engineering team. You will be responsible for designing, building, and maintaining scalable data pipelines and processing systems that support our business intelligence, analytics, and machine learning initiatives. Responsibilities
Develop and maintain scalable, robust data pipelines using Scala and big data technologies Work with large datasets from multiple sources to ingest, transform, and make data available for analytics and reporting Collaborate with Data Scientists, Analysts, and other engineers to understand data requirements and deliver efficient solutions Optimize ETL jobs for performance and cost Ensure data quality, governance, and consistency across all environments Monitor production jobs, troubleshoot issues, and ensure system reliability Implement best practices for data engineering, including code reviews, testing, and documentation Required Qualifications
Bachelor\'s or Master\'s degree in Computer Science, Engineering, or related field 6+ years of experience as a Data Engineer or in a similar role Strong skills in PySpark and SQL (experience with functional programming is a plus) Hands-on experience with big data tools like Apache Spark, Kafka, Hadoop, or Hive Proficiency in building ETL pipelines and working with structured and unstructured data Experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services Familiarity with version control systems (e.g., Git), CI/CD, and DevOps practices Solid understanding of data warehousing and data modeling concepts Preferred Qualifications
Knowledge of SQL and database systems such as Postgres, Redshift, or Snowflake Exposure to containerization technologies like Docker and orchestration tools like Airflow or Kubernetes
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