Rahul Sharma

• Doing data maturity assessment to define As-Is and To-Be plan to define data governance & quality strategy
• Organization wide ownership of data analytics solutions including defining KPIs and processes
• Engineering Manager as well as product owner for in-house Data Validation tool- that checks quality of data during ETL process at scale. The scale of 4 data quality tests every second i.e. more than 2.4 million test executions every week
• Managing a team of 8 data engineer, building scalable tools, frameworks and making positive impact for data producers and data consumers
• Bring enhancement for in-house data catalogue tool (DataMarket) and roll our open-source data governance tool OpenMetadata
• Define roadmap and data quality strategy for Agoda data ecosystem
• Organization wide ownership of data quality tools, KPIs and processes
• Increase data maturity among data producers and data users
• Saved $95,000+ (USD) in processing cost at Hadoop system based on cost-value matrix (as part of Data Governance)
• Share knowledge using "Tech Talk" forum to internal audience and international conference
• Increase data maturity among data producers and data users
• Managed multiple high stack projects and communicated effectively to both technical and non-technical audiences, conveying project needs, risks, delays, and outcomes clearly
• Managed cross-functional teams to ensure successful completion of projects within timeframes and budgets
• Working as well as product owner for in-house Data Quality & Governance tools

• Define data quality management framework, process, policy and do onboarding for data domains like ‘Hotel Data’, ‘Event Data’ for Data Quality Management
• Detail definition of Data Quality Framework for all steps from Definition Assessment Analysis Improvement Implementation Control
• Catalogue key data elements across data domains and perform data validation across various stage of data.
• Detail definition of Data Quality Framework for all steps from Definition -to- Assessment -to- Analysis -to- Improvement -to- Implementation -to- Control. Develop data quality/validation templates as part of framework.
• Develop data quality/validation templates as part of framework
• Define DQ/DG strategy based on DAMA recommendation
• Define process & perform analysis by using data extraction (ETL) and BI dashboards/reports
• Proficient in effective communication, conveying information persuasively and engagingly through various methods
• Skilled in problem-solving and decision-making, identifying issues, gathering information, evaluating alternatives, and choosing appropriate courses of action
• Determined root cause of data quality errors and recommended long-term solutions.

• Define & operationalized data quality framework and perform data validation at source, data in transit, during ETL and at reporting layer
• Lead data analytics program started as part of data strategy to enable OSN as data driven organization
• Enrich data governance framework and include data quality, data classification and metadata management
• Develop policy, standards, processes and KPIs for data governance, data quality and other data management & data analysis projects
• Member of different organization level committees like Data Council and DG Working Group
• Analyzed collected information from database reports to identify potential issues or discrepancies.

• Design and define the technical solution for data quality framework for data profiling, data cleansing and data monitoring
• Leads end-to-end process and methods supporting all areas of data quality and Unified Data Model (UDM) using snowflake schema as part of dimension modelling
• Define & apply data cleansing techniques that include cleansing data at source, data enrichment and standardization
• Utilized reporting tools like Tableau and Power BI to generate graphical representations of complex datasets for stakeholders' review
• Developed and implemented data quality control processes for large datasets including validation checks, error correction rules and procedures
• Analysed customer feedbacks through surveys and identified areas of improvement related to data quality issues.
• Identified control gaps in processes, procedures and systems through in-depth research and assessment and suggested methods for improvement.

• Managed daily operations involving the collection, manipulation, valid trends
• Storage and distribution of master data records
• Cleaned and manipulated raw data using different tools
• Reviewed existing reports and generated recommendations on how they can be improved exception and maintained data models to analyse large volumes of customer data
• Created custom dashboards and reports using Tableau to visualize data trends
• Partner with cross-functional team to define enterprise-wide data quality and master data framework requirements
• Work on multiple Master Data domains like Supplier Master Data (SMD), Legal Entity MD, Facility MD, Organization MD, and others
• Define and implement data governance process for addressing on-going data quality exceptions
• Works closely with customers to capture, analyses and document business and functional requirements
• Built interactive dashboards with drill down capabilities allowing users to explore underlying data points.
• Validated results and performed quality assurance to assess accuracy of data.

Multiple Projects

Project / Client - Reliance Life DQM & MDM (Feb’12 – Nov’12)

Project / Client - SAS UK – Onsite (Mar’11 – Jan’12)

Project / Client - First Bank of Nigeria (Onsite Nigeria) (May’10 – Feb’11)

Project / Client - SAS ETL & BI Solution (Aug’09 – Apr’10)

Multiple Projects

Project / Client - Fullerton India - Data Quality Solution (Dec’08 – Jul’09)

Project / Client - Vodafone Data Quality Solution (Dec’06 – Dec’08)