Job description
Job Title: Principal Data and Integration Engineer
Duration: 7 months
Location: Remote
Job Description Summary:
As a Data Warehouse Engineer you should have a strong understanding of ETL (extract, transform, load) concepts and will:
- Analyze, evaluate and design/redesign business, IT, and operational processes using scientific approaches such as Critical Thinking, Lean Management, Design Thinking and structured systems analysis and design.
- Have a strong background in data analysis from multiple disparate systems, tools, and methodologies such as Agile, Waterfall, Oracle, or SQL Server.
- Strong understanding of Normalized/Dimensional model disciplines and similar data warehousing techniques.
- Strong experience working with ETL/ELT concepts of data integration, consolidation, enrichment, and aggregation in large volume data sets.
- Expert in SQL and/or SQL-based languages and performance tuning of SQL queries.
- Working knowledge of Data Pipelines, stream processing and highly scalable ‘big data’ data stores.
- Experience with various data storage technologies - e.g. RDBMS (Oracle, SQL Server, etc.), columnar, tabular, document store, NoSQL
- Experience with various ETL/ ETL tools – e.g. SSIS, Informatica Power Center, SnapLogic etc.
- Experience with cloud-based data warehouses - e.g. Snowflake, BigQuery, Azure Synapse, RedShift, etc
- Experience with Python and SQL.
- Create supporting documentation, such as metadata and diagrams of entity relationships, business processes, and process flow.
- Collaborate with business users on normalizing and aggregating large data sets based on business needs and requirements.
- Data validation skills to verify data integrity, understand discrepancies, and resolve them with the highest sense of urgency.
- Demonstrated ability to share findings with non-technical or business stakeholders.
- Excellent problem solving skills
- Be an excellent communicator and passionate about your role.
In this role, your responsibilities & qualifications will include:
- Work with other data engineers and analysts to build new and extend existing data structures.
- Develop, maintain, and support ETL processes for loading data from multiple data sources into a Redshift data warehouse
- Design framework and metadata standards and make suggestions for data model improvements.
- Maintain large, multi-terabyte data warehouse which includes performance tuning and data retention/purge processes
- Research and troubleshoot data quality issues, providing fixes and proposing both short- and long-term solutions
- Data modeling experience for both transactional and data warehousing environments including familiarity with
- Kimball dimensional and 3NF modeling standards
- Experience working with a variety of data sources such as MySQL, Oracle, SQL Server, PostgreSQL, S3
- Supporting business-critical systems using mature IT and software engineering practices.
- Monitoring and Supporting ETL Job failures.
- Delivery of the highest quality product.
- Developing a deep understanding of the applications supported.
- Excellent communication skills with all levels of management.
- Strong SQL skills.
- Strong organization skills with the ability to handle multiple tasks simultaneously and the flexibility to shift priorities as needed.
Required skills:
- strong background in data analysis from multiple disparate systems, tools, and methodologies such as Agile, Waterfall, Oracle, or SQL Server
- Working knowledge of Data Pipelines, stream processing and highly scalable ‘big data’ data stores.
- Strong experience working with ETL/ELT concepts of data integration, consolidation, enrichment, and aggregation in large volume data sets.
- Experience with Python
- Expert in SQL and/or SQL-based languages and performance tuning of SQL queries.
- Strong experience in designing, building and maintaining high quality, secure software in IT.
Job Type: Contract
Schedule:
- Monday to Friday
Experience:
- ETL/ELT: 5 years (Required)
- Data warehouse: 6 years (Required)
- Data Pipelines: 5 years (Required)
Work Location: Remote
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