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Company Profile

Overview


Since year 2003, Oceaneering’s India Center has been an integral part of operations for Oceaneering’s robust product and service offerings across the globe. This center caters to diverse business needs, from oil and gas field infrastructure, subsea robotics to automated material handling & logistics.


Our multidisciplinary team offers a wide spectrum of solutions, encompassing Subsea Engineering, Robotics, Automation, Control Systems, Software Development, Asset Integrity Management, Inspection, ROV operations, Field Network Management, Graphics Design & Animation, and more.


In addition to these technical functions, Oceaneering India Center plays host to several crucial business functions, including Finance, Supply Chain Management (SCM), Information Technology (IT), Human Resources (HR), and Health, Safety & Environment (HSE).


Our world class infrastructure in India includes modern offices, industry-leading tools and software, equipped labs, and beautiful campuses aligned with the future way of work. Oceaneering in India as well as globally has a great work culture that is flexible, transparent, and collaborative with great team synergy.


At Oceaneering India Center, we take pride in “Solving the Unsolvable” by leveraging the diverse expertise within our team. Join us in shaping the future of technology and engineering solutions on a global scale.






Position Summary

Position Summary and Location


Responsible for identifying data quality issues, analyzing data sets, and working with various teams to improve data quality across the organization.






Duties & Responsibilities

Duties and Responsibilities


Key Responsibilities:


·Perform data profiling and analysis to assess the quality of data across different systems and sources.


·Identify and report data quality issues, including missing, duplicate, or inconsistent data, and recommend corrective actions.


·Monitor data quality KPIs (e.g., completeness, accuracy, timeliness, consistency) and track improvements over time.


·Implement data quality checks and validation rules to ensure that data meets the organization’s standards.


·Collaborate with data stewards, business analysts, and other teams to perform data cleansing activities, including data correction, enrichment, and de-duplication.


·Support the development and implementation of data standardization practices across the organization to ensure consistency in data entry and processing.


·Conduct root cause analysis of data quality issues and work closely with technical teams to identify and resolve the underlying problems.


·Track recurring data quality issues and develop long-term strategies to prevent them from reoccurring.


·Work with data governance and infrastructure teams to implement automated processes to improve data quality.


·Support data governance initiatives by helping define and enforce data quality standards, policies, and procedures. Document data quality processes and contribute to data governance documentation, including data dictionaries and metadata management.


·Collaborate with data engineering, data management, business intelligence, and IT teams to implement data quality best practices.


·Work with business units to understand their data needs and ensure data quality processes align with business objectives.


Supervisory Responsibilities


·This position has/does not have direct supervisory responsibilities.


Reporting Relationship


Sr. Manager, Data Estate – Business Intelligence






Qualifications

Qualifications


·Bachelor’s degree in data management, Information Systems, Computer Science, Statistics, or a related field.


·Certification in Data Quality, Data Governance, or a similar area is a plus.


Experience:


·2+ years of experience in data quality analysis, data management, or data governance.


·Experience with data profiling, cleansing, and validation tools (e.g., Informatica Data Quality, Talend, Microsoft Purview, Trillium).


·Strong proficiency in SQL for querying and analyzing large datasets.


Knowledge, Skills, Abilities, and Other Characteristics


·Strong understanding of data quality dimensions (accuracy, completeness, consistency, uniqueness, and timeliness).


·Experience with data profiling and analysis techniques to identify data anomalies and issues.


·Ability to perform data validation, root cause analysis, and data cleansing tasks.


·Proficiency in data visualization and reporting tools like Tableau, Power BI, or Excel.


·Strong analytical skills with the ability to problem-solve and make data-driven recommendations.


Excellent attention to detail and ability to handle complex data sets.


Preferred Qualifications:


·Experience with data governance tools or data catalog systems (e.g., Collibra, Alation).


·Familiarity with cloud-based data platforms (e.g., AWS, Azure, Google Cloud).


·Knowledge of data privacy and compliance regulations (GDPR, CCPA) and how they impact data quality practices.






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