Senior Python Data Analyst Jobs in Affton, MO (NOW HIRING)

The position of Sr. Business Intelligence Data Analyst/Engineer - must possess a solid knowledge of the principles and practices of enterprise data warehouse development, data modeling and testing and story-telling through data analytics.

• Serve as an internal data consultant, participating in data integration discussions.
• Participates in the design, development, validation and testing of new or revised reports. Works with user to verify results and content, develops error or exception reports when applicable and receives user sign off on completed work.
• Analyze and evaluate highly complex business and market data; interpret data for the purpose of determining organizational/program performance, trends and/or probability.
• Design and apply forecasting and predictive modeling techniques to enhance strategic thinking and business planning.
• Efficiently and effectively operate across multiple projects simultaneously and assume responsibility for the appropriate data/information architecture, design and quality.
• Meet with key stakeholders to present and review data output to improve operational performance, support decisions, and enhance planning efforts.
• Mentor and train on the appropriate usage of data marts, enterprise data warehouse and other data sources used in reporting and analytics, including reporting and visual use cases.
• Uses and promotes established Software Development Life Cycle (SDLC) standards, QA and change control procedures.
• As a member of the Data Warehouse Team, you will be involved in all aspects of:
  • Designing, implementing, maintaining, and supporting end-to-end ETL solutions, as well as data warehouse and cubes.
  • Developing, refining and maintaining the security, quality and integrity of data in ETL solutions and the data warehouse at large.
  • Establishing, implementing and upholding data integration standards and methodologies.
  • Creating and executing test plans for ETL and data integration solutions
  • Monitoring ETL jobs to verify execution, maintain performance and resolve data integration issues as they arise.
  • Implementing, maintaining and supporting the data quality, data catalog and master data management initiatives of data marts and the enterprise data warehouse system.
  • Working with Database and System Administrators to establish and enforce best practices for availability, performance, and data security.
  • Proactively designing support activities around data integration; such as on-going data validation and performance tuning.
  • Participating in code and design review to ensure alignment to standards and best practices.
  • Reviewing existing data structures and recommend optimizations and redesigns, as warranted.
• Serves as a technology advocate throughout the IT organization to help promote the effective use of the data/information architecture to meet business needs and to build sustained competitive advantage for the enterprise.

• Serve as an internal data consultant, participating in data integration discussions.
• Participates in the design, development, validation and testing of new or revised reports. Works with user to verify results and content, develops error or exception reports when applicable and receives user sign off on completed work.
• Analyze and evaluate highly complex business and market data; interpret data for the purpose of determining organizational/program performance, trends and/or probability.
• Design and apply forecasting and predictive modeling techniques to enhance strategic thinking and business planning.
• Efficiently and effectively operate across multiple projects simultaneously and assume responsibility for the appropriate data/information architecture, design and quality.
• Meet with key stakeholders to present and review data output to improve operational performance, support decisions, and enhance planning efforts.

• Mentor and train on the appropriate usage of data marts, enterprise data warehouse and other data sources used in reporting and analytics, including reporting and visual use cases.
• Uses and promotes established Software Development Life Cycle (SDLC) standards, QA and change control procedures.
• As a member of the Data Warehouse Team, you will be involved in all aspects of:
  • Designing, implementing, maintaining, and supporting end-to-end ETL solutions, as well as data warehouse and cubes.
  • Developing, refining and maintaining the security, quality and integrity of data in ETL solutions and the data warehouse at large.
  • Establishing, implementing and upholding data integration standards and methodologies.
  • Creating and executing test plans for ETL and data integration solutions
  • Monitoring ETL jobs to verify execution, maintain performance and resolve data integration issues as they arise.
  • Implementing, maintaining and supporting the data quality, data catalog and master data management initiatives of data marts and the enterprise data warehouse system.
  • Working with Database and System Administrators to establish and enforce best practices for availability, performance, and data security.
  • Proactively designing support activities around data integration; such as on-going data validation and performance tuning.
  • Participating in code and design review to ensure alignment to standards and best practices.
  • Reviewing existing data structures and recommend optimizations and redesigns, as warranted.
• Serves as a technology advocate throughout the IT organization to help promote the effective use of the data/information architecture to meet business needs and to build sustained competitive advantage for the enterprise.

• Proficient use of Microsoft Data Analytics tools (SSIS, SSAS, SSRS, Power BI) as well as Microsoft Office tools.
• Deep knowledge and practical use of Microsoft Querying Languages, including TSQL, MDX, DAX.
• Proven ability to design, develop, test and deploy efficient and effective tabular and multidimensional cubes, along with necessary ETL code and processes to support them.
• Possess in-depth knowledge with one or more BI visualization tools including but not limited to: SSRS, Power BI, Qlik Sense, QlikView, Tableau, SAS Business Intelligence, SAP BusinessObjects BI, MicroStrategy, IBM Cognos Analytics, Sisense, ThoughtSpot, or Google Analytics.
• Demonstrated experience planning, designing, developing and delivering end-to-end BI/Data Analytics solutions (i.e. – data warehouses, data/ information delivery)
• Requires proven analytical skills with ability to organize, maintain, process and analyze vast amounts of information and complex issues and communicate findings in a clear, concise manner including verbally, graphically and in writing to a variety of audiences.
• Ability to utilize critical thinking and project management skills to manage work efforts through to successful completion.
• Independent problem-solving skills and data analysis techniques required.
• Requires demonstrated ability to organize and execute work independently and effectively within frequent deadlines.
• Excellent written, verbal communication and presentation skills are required.
• Ability to establish and build relationships with all members of the business community are required.
• Requires ability to maintain effective interpersonal skills with internal and external staff and audiences.
• In-depth knowledge of relational databases, cubes, data consumption, and advanced data analysis.
• Ability to lead data exploration with key stakeholders to draw conclusions and make data driven business decisions.
• Bachelor’s Degree in Computer Science, Information Systems, or other related field, or 7+ years equivalent work experience required.
• Minimum of 7 years’ experience designing, developing and tuning complex, large (TB) database management systems in support of operational reporting, decision support, complex data analysis and system integration.
• Minimum of 7 years’ experience working with and tuning Microsoft SQL Server or other similar relational database management systems.
• Minimum of 7 years’ experience in data modeling, database design (multi-dimensional and data warehouse), data integration and ETL.

• Bachelor’s Degree in Computer Science, Information Systems, or other related field, or 7+ years equivalent work experience required.
• Minimum of 7 years’ experience designing, developing and tuning complex, large (TB) database management systems in support of operational reporting, decision support, complex data analysis and system integration.
• Minimum of 7 years’ experience working with and tuning Microsoft SQL Server or other similar relational database management systems.
• Minimum of 7 years’ experience in data modeling, database design (multi-dimensional and data warehouse), data integration and ETL.

• High degree of self-motivation, drive and determination, along with high aptitude.
• Master’s Degree is preferred.
• Supply chain industry experience preferred.
• Knowledge of and experience with cloud data solution offerings (Azure Data Lake, Data Factory, Data Management Gateway, Azure Storage Options, DocumentDB, Data Lake Analytics, Stream Analytics, EventHub, Azure SQL, etc.)
• Experience with big data tools: Hadoop, MapReduce, HBase, oozie, Flume and Pig.
• Experience and knowledge of cost-optimized cloud deployments spanning compute, network and storage.
• Experience of message queuing, stream processing and highly scalable big data stores.
• Experience with NoSQL databases, such Cassandra, MongoDB, CosmosDB.
• Experience working with DevOps tools: ADO, Git, Jenkins, Dockers, etc.
• Experience with stream-processing systems: Storm, Spark-Streaming, etc.
• Experience in creating advanced statistics such as: regression, clustering, decision trees, exploratory data analysis methodology, simulation, scenario analysis and modeling.
• Experience/ keen interest in exploring latest technologies and programming languages.
• Have strong interest in future path of to design, develop and support Machine Learning technologies, algorithms and models in support of business initiatives including:
  • Determine the appropriate algorithms to solve a given problem through testing, analysis, and validation with the business.
  • Data exploration and visualization to understand and define features for a given data set.
  • Data model training and tuning to reduce errors and increase reliability and accuracy.
  • Participate in innovation forums to identify new ways to leverage data to solve business issues.