Data Integration Specialist

HYBRID ON SITE REQUIRED: Expected 2 days on site and 3 days remote Clear Communication skills is important Skill matrix: Skill Years of experience • 7 years of experience with Data Engineering, working with large-scale data processing and ETL pipelines. • 5 years of hands-on experience with data modeling, architecture and management. • 5 years of experience with Relational Database Systems, Data Design, RDBMS Concepts, ETL • 5 years of experience working with data in cloud environments such as AWS (preferred), Azure, GCP • 3 years of experience in T-SQL, SQL, ELT/ETL performance tuning. • Programming experience in Snowflake, Hadoop, or other Data Warehouse technologies; Snowflake preferred. • Experience in Microsoft SQL Server 2008R2 or newer. • Experience with SSIS or equivalent ETL tool. • Experience in SQL/Stored Procedure development. Data Integration Specialist Description of Work: • Worked with advanced technical principles, theories, and concepts; well versed in technical products; able to work on complex technical problems and providing innovative solutions; and can work with highly experienced and technical resources. • Demonstrates ability to communicate technical concepts to non-technical audiences both in written and verbal form. • Assembles large, complex data sets to meet business requirements. • Works in tandem with Data Architects to align on data architecture requirements provided by the latter. • Creates and maintains optimal data pipeline architecture. • Identifies, designs, and implements internal process improvements: automating manual processes, optimizing data delivery. • Implements big data and NoSQL solutions by developing scalable data processing platforms to drive high-value insights to the organization. • Supports development of Data Dictionaries and Data Taxonomy for product solutions. • Demonstrates strong understanding with coding and programming concepts to build data pipelines (e.g., data transformation, data quality, data integration, etc.). • Builds data models with Data Architect and develops data pipelines to store data in defined data models and structures. • Demonstrates strong understanding of data integration techniques and tools (e.g., Extract, Transform, Load (ETL) / Extract, Load, Transform (ELT)) tools and database architecture. • Demonstrates strong understanding of database storage concepts (data lake, relational databases, NoSQL, Graph, data warehousing). • Identifies ways to improve data reliability, efficiency, and quality of data management. • Conducts ad-hoc data retrieval for business reports and dashboards. • Assesses the integrity of data from multiple sources. • Manages database configuration including installing and upgrading software and maintaining relevant documentation. • Monitors database activity and resource usage. • Performs peer review for another Data Engineer's work. • Assists with development, building, monitoring, maintaining, performance tuning, troubleshooting, and capacity estimation. • Sources data from the operational systems. • Prepares the database-loadable file(s) for the Data Warehouse. • Manages deployment of the data acquisition tool(s). • Monitors and maintains Data Warehouse/ELT. • Monitors, reports, and resolves data quality. • Works closely with all involved parties to ensure system stability and longevity. • Supports and maintains Business Intelligence functionality. • Evaluates, understands, and implements patches to the Data Warehouse environment. • Loads best practices and designs multidimensional schemas. • Attend all customer technical discussions/design/development meetings and provide technical inputs to further enhance the code quality/process. • Provide guidance/support to other junior/mid-level developers. • Impact functional strategy by developing new solutions, processes, standards, or operational plans that position Leidos competitively in the marketplace. • All other duties as assigned or directed.