Role: Lead Business Data Analyst
Location: Sunnyvale, CA or Austin, TX (5x/ week onsite)
Duration: 6+ Months with possible extension
Must have experience:
10+ years of experience in data analytics, business analysis and data management. Advanced SQL expertise, Proficiency in Python for data analysis, transformation, and feature engineering (Pandas, NumPy). Exp with Tableau or similar BI visualization tools for storytelling and dashboards. Deep understanding of data architecture, governance, MDM, and data lineage. Proven track record in identifying and scoping new data use cases and converting insights into business recommendations. Strong analytical thinking, stakeholder management, and communication skills. Experience with Snowflake, Databricks, or Hadoop/Spark environments.
Tooling Stack: SQL (PostgreSQL, Snowflake, Redshift), Python (Pandas, NumPy, feature engineering), Tableau for visualization, Git / Bitbucket for version control, JIRA / Confluence for project tracking and documentation
Data Analysis Insight Generation Perform in-depth analysis of enterprise data to uncover trends, patterns, and correlations. Identify actionable insights and data-driven opportunities that inform decision-making and strategic initiatives. Data Use Case Identification Collaborate with stakeholders to identify and define data use cases across functional domains, ensuring alignment with business priorities and future-state data strategy. Business-to-Technical Translation Engage with stakeholders to translate business requirements into clear technical specifications, analytical models, and actionable deliverables. Impact Assessment Analyze current-state data and infrastructure versus future-state goals identify data and process gaps define mitigation strategies. Data Profiling Quality Analysis Perform deep dives into structured and semi-structured datasets to assess completeness, consistency, and accuracy work with SMEs to understand data availability and source gaps. Data Integration Transformation Design and validate
data pipelines and transformations document lineage and dependencies. Feature Engineering Analytics Use Python and SQL to extract, clean, and engineer data features for analytics and modeling. Reporting Visualization Build and maintain insightful Tableau dashboards and reports to communicate findings effectively. Governance Documentation Maintain business glossary, data dictionary, and metadata aligned with governance standards. Testing Validation Participate in validation of new or transformed data sets to ensure integrity and alignment with business requirements. Knowledge Management Maintain the data dictionary and business glossary for assigned domains, capturing and documenting definitions aligned with business leadership and global teams. Cross-functional Collaboration Partner closely with data engineers, product managers, and business SMEs to align solutions with business objectives.
Required Skills Qualifications 8-12 years of experience in data analytics, business analysis, or data management. Advanced SQL expertise with ability to query and optimize large, complex datasets. Proficiency in Python for data analysis, transformation, and feature engineering (Pandas, NumPy).Experience with Tableau or similar BI visualization tools for storytelling and dashboards. Deep understanding of data architecture, governance, MDM, and data lineage. Proven track record in identifying and scoping new data use cases and converting insights into business recommendations. Strong analytical thinking, stakeholder management. Experience with Snowflake, Databricks, or Hadoop Spark environments. Exposure to data catalog or governance tools (Collibra, Alation).Familiarity with DB data hierarchy, enrichment, or similar reference data systems. Environment Tooling Stack SQL (PostgreSQL, Snowflake, Redshift)Python (Pandas, NumPy, feature engineering)Tableau for visualization JIRA Confluence for Project Tracking Git Bitbucket
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Thanks & regards, Clark (Sonu Chauhan) |
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Technical Recruiter |
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Email: sonuc@sysmind.com |
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