Collaborate with cross-functional teams to drive data enablement and data driven business decisions ensuring seamless integration and minimal disruption to daily operations
Leverage Google Cloud Platform (GCP) services like BigQuery and Cloud Storage for efficient data warehousing, processing, and analytics at scale
Identify, document, analyze, and communicate requirements for reporting analytics and decision support tools
Conduct thorough analysis of data to identify patterns, anomalies, and signs of corruption
Design, develop and maintain our reporting infrastructure using the various reporting stacks including Power BI, SSRS, Tableau, Looker, and QlikSense
Lead efforts to apply software engineering best practices to analytics solutions
Lead the efforts for platform documentation, version controlling, and production releases
Utilize understanding of multiple data structures and sources to design, develop and implement decision support solutions, including data visualization, business intelligence, or data collection
Conduct research and analysis of business situations to contextualize and summarize data for end users
Develop innovative approaches to address complex data issues and business problems
Collaborate with internal stakeholders to define business requirements and uses those requirements to develop business intelligence reports
Evaluate business needs and objectives to inform your data architecture design solutions
Analyze data from internal and external sources to ensure accurate data for analysts & business consumption
Lead the effort to translate business needs into requirements to recommend and build reporting solutions
Responsible for companywide Operational Readiness Production Testing reporting including requirement traceability, development completion rate, defect close rate, and ELT readout dashboards
Support business case development with cost/benefit analysis for continuous funding and prioritization
Drive a scalable and robust cross-domain E2E transformation through consistent metrics, reporting, analytics and predictive data science for Consumer and Business markets
Requirements
Bachelor's degree in Statistics, Computer Science, MIS, or a similar quantitative field (preferred)
5+ years of relevant experience as a data analyst, data engineer, BI developer, or BI analyst with a strong technical foundation
Hands-on development experience with at least one of the leading reporting tools, including Power BI, SSRS, Tableau, Looker, and QlikSense
Solid experience in scripting with SQL, Python, JSON, LookML, JavaScript, and/or R
Solid understanding of best engineering practices for the full software development life cycle (SDLC), including coding standards, code review, source control, build, test, deploy, and operations
Deep understanding of data warehousing concepts, database designs and data architecture
Datawarehouse experience with GCP, Azure, or SSMS
Experience with big data technologies and advanced data analytics
Good written and verbal communication skills
Strong analytical and problem-solving skills
Ability to work in a fast-paced environment concurrently on multiple projects with varying deadlines
Commitment to excellence - quality, detail and deadline driven
AI experience with a variety of data science and big data tools (R, Python, SPARK, etc.)
Benefits
Competitive medical, dental, vision, and life insurance
Employee assistance program
401K plan with company match
Voluntary benefits
Paid time off
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
data analysisdata engineeringbusiness intelligence developmentreporting toolsSQLPythonJSONLookMLJavaScriptR
Soft skills
communication skillsanalytical skillsproblem-solving skillsability to work under pressurecommitment to excellencecollaborationdocumentationrequirements analysisinnovationbusiness case development