DATA ANALYST PRINCIPAL
Provides thought leadership, coaching and direction of data analysts across the organization. Uses advanced statistical skills to interpret data and turn it into information which can offer ways to improve how the data is used within the business, thus affecting business decisions. Collaborates with solution architects to integrate data analysis quality solutions to production processes. Reports back findings in a comprehensive study to senior leadership. Responsible for championing improvement of overall data quality and data process methods.
Provides thought leadership, develops strategies and methods for analyzing and profiling data, and assists lower level Data Analysts in application of methods to ensure the effectiveness and efficiency of data analysts globally.
Summarizes descriptive and diagnostic analytics on data sources and reviews results with senior leadership.
Identifies needs to develop and introduce new machine learning tools to improve data analysis processes and results.
Applies high level analytical techniques on data sets to find patterns and anomalies in data sets.
Creates techniques and standards for visualizations and dashboards to help the company interpret and make decisions with the data; creates complex reports and dashboards on analysis results applying advanced capabilities of business intelligence tools and technologies.
Analyzes complex, diverse data sets from multiple sources to identify data quality, coherency and integrability issues and reduce data redundancy; provides recommendations and designs solutions to resolve issues throughout the data lifecycle.
Uses data analysis results at all levels to provide recommendations and designs solutions to improve data management processes and resolve data issues.
Supports data and data governance audits within assigned domains; works proactively to identify and resolve compliance issues ahead of audit; ensures compliance to data governance requirements aligned with data owner and business objectives.
Determines how Data Cataloging tools support Data Analysis and integrate into the overall process for ensuring data quality.
Establishes metrics and measures for data quality.
Data Literacy – Expresses data in context, including data sources and constructs, analytical methods and applied techniques; describes the use-case application and resulting value.
Data Profiling – Assesses data issues and cleansing requirements to perform data extraction, mapping, collection, and testing; establishes good, quality data.
Data Communication and Visualization – Constructs a tale of the business problem, root cause, solution options, and opportunities through illustrating data visually, including reports and dashboards.
Data Quality – Identifies, understands and corrects flaws in data that supports effective information governance across operational business processes and decision making.
Project Management – Establishes and maintains the balance of scope, schedule and resources for a temporary effort (a “project”).
Data Analytics – Discovers, interprets and communicates qualitative and quantitative data; determines conclusions relying on knowledge of business or functional frameworks; simultaneously applies statistics, data validity, data visualization, and problem solving approaches to effectively extract meaningful patterns and business insights; presents conclusions and outcomes that enable data driven business decisions.
Communicates effectively – Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences.
Customer focus – Building strong customer relationships and delivering customer-centric solutions.
Tech savvy – Anticipating and adopting innovations in business-building digital and technology applications.
Balances stakeholders – Anticipating and balancing the needs of multiple stakeholders.
Action oriented – Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
Manages ambiguity – Operating effectively, even when things are not certain or the way forward is not clear.
Education, Licenses, Certifications
College, university or equivalent degree preferred or equivalent work experience in relevant technical discipline.
This position may require licensing for compliance with export controls or sanctions regulations.
Significant experience in a relevant discipline is required. Knowledge of the latest technologies and trends in data science is highly preferred and includes:
Advanced methods, tools and solutions for analyzing and profiling data
SQL query language execution on NOSql and SQL sources
Exposure to Agile software development
Exposure to IoT technology
Data profiling tools, technologies and coding
Data Catalog tools and technologies
Business intelligence tools and technologies
Significant experiences in the following are preferred:
Understandour enterprise data and the associated processes.
Understand legacy implementation and chart data modelling approach formigration and modernization
Design data model for various functional areas of the data platform.
Collaborate with data engineers, solution architects other stakeholders on thedata model, maintenance and optimization.
Work with Product Owner/Business Analysts to understand functional requirementsand interact with other cross-functional teams to architect the data model.
Support Data Load and Data fixes
Create and maintain data dictionaries and associated lineage details for datamodel.
Perform Technical Mapping and Field Analysis.
Influence and review key design decisions to enable program implementation
Be a thought leader and a partner who bridges the gap between business andtechnology forging cross-functional relationships and working consultativelywith business stakeholders, data engineering, reporting, data science,analytics and security teams.
Navigate challenges to solve complex business problems.
Proficientin an Azure analytics environment encompassing RDBMS (SQL/Oracle), Big datastorage and computing environments. Understanding of ADLS, Databricks, spark desirable.
Experience with data management in Cloud data warehousing tools, (Snowflake ispreferred).
Knowledge of supply chain, finance and manufacturing domains will be beneficialfor the role.
Proficient in Erwin or similar type data modeling software.
Significant experience in Data Quality practices and techniques
Experience SQL query language are desired. Spark knowledge willhelp.
Significantexperience in data modelling and data architecture is required. 10-12 years ofexperience in BI and Analytics projects, data migration, data modelling (Usingvarious strategies like data vault, 3NF, dimensional models etc), dataarchitecture (Including but not limited to understanding of data flows,migration approaches, ETL code build process, metadata, performance anddatabase management is expected)
Job SYSTEMS/INFORMATION TECHNOLOGY
Primary Location India-Maharashtra-Pune-India, Pune, IOC Tower A
Job Type Experienced – Exempt / Office
Recruitment Job Type Exempt – Experienced
Job Posting Sep 21, 2022, 4:37:10 AM
Unposting Date Jan 4, 2023, 1:29:00 PM
Req ID: 220007YZ