Data Engineer
Job Title: Data Analyst II
Locations: Washington DC (Onsite)
Duration: 12 Months Contract on W2 (Possible extension)
We are seeking a highly skilled and experienced Data Analyst to join our client's Data Engineering team. As a key team member, you will be responsible for providing data analysis support to Global Operations across the organization. Your primary focus will be on resolving privacy tasks, on-call tasks that require backfilling, tracking tasks, creating bug intake forms, and deprecating stale tables.
Must-Have Skills:
• 2+ years of experience in developing ETL pipelines, modifying existing databases, and database management systems
• Strong SQL skills AND experience with data visualization tools such as Tableau or Power BI
• Knowledge of data warehousing concepts and ETL processes
Nice-to-have Skills:
• Familiarity with Client's data infrastructure and tools (e.g., Hive, Presto, Spark)
• Experience with data governance and data quality best practices
• Experience with Python programming language
Responsibilities:
Maintain and build documentation for data assets (pipelines and dashboards) developed by the Data Engineering team
Resolve privacy issues and implement data quality checks where applicable
Ensure timely availability of data tables
Deprecate tables with 0 usage or stale data and identify next tables for deprecation
Requirements:
2+ years of experience in developing ETL pipelines, modifying existing databases, and database management systems
Strong SQL skills
Knowledge of data warehousing concepts and ETL processes
Experience with data visualization tools such as Tableau or Power BI
Excellent problem-solving skills and attention to detail
Ability to work independently and collaboratively as part of a team
Strong communication and interpersonal skills
Nice to Have:
Familiarity with client's data infrastructure and tools (e.g., Hive, Presto, Spark)
Experience with data governance and data quality best practices
Experience with Python programming language
Experience with cloud-based data platforms (e.g., AWS, GCP, Azure)
Job Title: Data Analyst II
Locations: Washington DC (Onsite)
Duration: 12 Months Contract on W2 (Possible extension)
We are seeking a highly skilled and experienced Data Analyst to join our client's Data Engineering team. As a key team member, you will be responsible for providing data analysis support to Global Operations across the organization. Your primary focus will be on resolving privacy tasks, on-call tasks that require backfilling, tracking tasks, creating bug intake forms, and deprecating stale tables.
Must-Have Skills:
• 2+ years of experience in developing ETL pipelines, modifying existing databases, and database management systems
• Strong SQL skills AND experience with data visualization tools such as Tableau or Power BI
• Knowledge of data warehousing concepts and ETL processes
Nice-to-have Skills:
• Familiarity with Client's data infrastructure and tools (e.g., Hive, Presto, Spark)
• Experience with data governance and data quality best practices
• Experience with Python programming language
Responsibilities:
Maintain and build documentation for data assets (pipelines and dashboards) developed by the Data Engineering team
Resolve privacy issues and implement data quality checks where applicable
Ensure timely availability of data tables
Deprecate tables with 0 usage or stale data and identify next tables for deprecation
Requirements:
2+ years of experience in developing ETL pipelines, modifying existing databases, and database management systems
Strong SQL skills
Knowledge of data warehousing concepts and ETL processes
Experience with data visualization tools such as Tableau or Power BI
Excellent problem-solving skills and attention to detail
Ability to work independently and collaboratively as part of a team
Strong communication and interpersonal skills
Nice to Have:
Familiarity with client's data infrastructure and tools (e.g., Hive, Presto, Spark)
Experience with data governance and data quality best practices
Experience with Python programming language
Experience with cloud-based data platforms (e.g., AWS, GCP, Azure)
