Sr. Data Analytics Engineer

Company Description

SYSRS IT Services specializes in offering IT Services: Technology Services, Consulting Services, Software Solutions and Applications. Incorporated in 2013, SYSRS IT Services focuses on innovative and practical delivery of services to meet the critical IT missions of its clients.

At SYSRS IT Services, we are committed to serving our customers with a wide range of information technology services and solutions with guaranteed satisfaction, friendly and professional service, during convenient hours of operation, and resulting in a great onsite/offsite experience.

Job Description

Job Requisition:
Sr. Data Analytics Engineer
 

Job Description:
Leidos is seeking a Senior Data Analytics Engineer to develop a new data analytics platform service offering for a federal client. You will contribute to establishing the ingestion patterns, data storage patterns, data transformation methods, and data lake formation. You’ll support data architecture-related activities through business needs analysis and routine issue resolution, including data pipeline design and data lake solution design. Put your consulting expertise to use to drive our future Data Analytics platform.

Primary Responsibilities:

• Develop future state data architecture in consultation and alignment with the enterprise architecture team.
• Help the architecture team put together conceptual, logical, and physical data architecture and define the technical roadmap to the future state.
• Design data warehouse/data marts/data lakes/data hubs solutions and work with various data warehouse technologies to develop plans that best support the Program.
• In collaboration with technical leads and subject matter experts (SME), develop and manage architecture framework and design patterns of data analytics, integration, and visualization platform as per standards and industry best practices.
• Ability to analyze and evaluate new products as it relates to data lake/processing/analytics and suggest platform architecture modifications as necessary
• Participate in customer meetings to review business requirements and maintain the traceability of data sources and artifacts.
• Support data migration from the current state to the future state platform.
• Provide technical guidance and consultation and clarify technical and business requirements to development teams.
• Translate business needs into enterprise data architecture requirements and identify and forecast future state data architecture alternatives.
• Experiment with cloud-native, serverless tools and advise on new tools to determine optimal solutions given the requirements dictated by the use case.
• Expert in both traditional and modern data architecture and processing concepts, including relational databases, data warehousing, big data, NoSQL, and business analytics
• Show efficiency in handling data - tracking data lineage, ensuring data quality, and improving discoverability of data.
• Ability and desire to conduct hands-on data tool development work to complete proofs of concept
• Provide periodic briefings to peers and leadership on the state of the data architecture.
• Ability to multitask, problem-solving skills, and customer management skills are required.
• Ability and desire to work with other program staff and customers to reach design decisions within given constraints

Qualifications

Basic Qualifications:

• Candidate must have bachelor’s or master’s degree with prior relevant experience.
• Must have 8 years of Data Analytics experience.
• Experience in data pipeline architecture design, development, and optimization.
• Working experience or familiarity with AWS data analytics tools like Redshift, EMR, Data Lake Formation, AWS Glue, AWS Glue Brew, AWS Athena, Lambda, AWS Data Pipeline, Cognito, Quicksight, and S3.
• Experience with a variety of database technologies: RDBMS, NoSQL, search, data lakes.
• Experience with one or more visualization tools such as Power BI, Tableau, and Qlik.

Additional Information

Preferred Qualifications:

• Experience with AWS-specific data management and analytics strategies.
• Experience doing trade analysis on multiple data analytics tooling options supporting data lake and visualization layer.