Data Analytics Specialist

Description

• Bachelor’s degree in computer science or a related discipline, typically 8 or more years of solid, diverse work experience in IT with a minimum of 6 years’ combined experience in data science & data engineering implementations including DWBI application design, development, and implementation.
• Certification: AWS Solution Architect – Associate certified- The need to have relevant AWS data management experience is very crucial for the role.
• Good knowledge of Relational databases & Data warehouses (AWS Redshift & Oracle experience preferred), SQL, PL/SQL, and Functional experience in Tableau reports/dashboards.
• Strong technical skills to extract large amount of data through SAS/Teradata/Hadoop/Oracle/SQL and construct easy to use tools and reports using VBA/Tableau/R/Python/GIS (knowledge of or ability to learn Python required).
• Proficiency and Experience in tools such as Tamr, SageMaker and Jupyter Notebook is a plus.
• Ability to build models and manage the model building process (data prep, model build, validation, and implementation).
• Experience in other BI/reporting tools such as ThoughtSpot, OBIEE etc. will be a plus.
• Experience in documenting key deliverables such as Requirement Gathering, FIT/GAP Analysis, ETL specs, Business model design, Functional Design for Reports and Data Mapping.
• Strong experience on customization & implementations of Data Warehouses using ETL and BI Reporting tools.
• Have a strong understanding of the BI architecture including physical data models, ETL, logical business models and subject areas.
• Good communication & presentation skills
• Detailed Oriented and strong experience in performing Data analysis.
• Strong data management principles, around data architecture, modeling/design, data quality, security, data organization and operations.

Responsibilities

• • Apply Data Science principles to analyze large datasets, build ML models, and derive business value.
• • Partner with internal and external teams for functional and technical design of the Data Analytics platform.
• • Translate business needs into clear Data Analytics functional design documents.
• • Create data lineage mapping documents for data validation.
• • Review technical design documents to ensure alignment with best practices.
• • Develop ad-hoc reports and queries to support the business team.
• • Assist during testing phases and validate defects.
• • Perform extensive data analysis and summarize insights.
• • Utilize data science for actionable recommendations and create ML solutions.
• • Apply software engineering best practices.
• • Leverage tools like SQL, Hadoop, Spark, and Python.
• • Regularly engage with stakeholders.
• • Stay updated on analytic tools and techniques.
• • Ensure solutions align with existing processes.
• • Collaborate on pilots for testing new solutions.