Data Quality - BCBS239

Job Title: Data Quality - BCBS239 - Remediation Experience: 8–14 Years Location: Bangalore / Chennai Role Overview Capco is seeking experienced Data Quality (DQ) consultants to support a key client engagement focused on Data Quality transformation and regulatory compliance. The role involves delivering Data Quality Remediation & Transformation Plan (RTP) actions aligned to BCBS239 compliance and implementing DQ Management Standard 2.0. Key Responsibilities Implement and support Data Quality Management (DQM) framework across business and technology domains Perform data profiling, data validation, and data reconciliation across multiple banking datasets Identify data quality issues (completeness, accuracy, consistency, timeliness, validity) and escalate to stakeholders Support IMR (Issue Management & Remediation) by tracking, monitoring, and closing data issues Conduct root cause analysis (RCA) for recurring data quality problems Define and monitor Data Quality rules, metrics, and KPIs (DQI – Data Quality Index) Develop and maintain DQ dashboards and reports for management reporting Work with Data Stewards and Data Owners to define business rules and metadata definitions Support regulatory reporting (BCBS 239 / Risk / Finance data controls) Collaborate with cross-functional teams (Risk, Finance, Technology, CDO) for issue resolution Ensure adherence to data governance standards and enterprise data policies Required Skills & Experience 8-10 years of experience in Data Quality / Data Governance / IMR / Data Management Strong knowledge of banking domain (Risk, Finance, Regulatory Reporting preferred) Hands-on experience in SQL for data analysis and validation Experience in data profiling, data cleansing, and data reconciliation Understanding of data quality dimensions (accuracy, completeness, consistency, timeliness) Experience in issue management (IMR / Jira / ServiceNow or similar tools) Strong RCA (Root Cause Analysis) and analytica

Role Overview You’ll help global clients keep their most critical corporate governance data accurate, secure, and easy to use. As a Professional Services Data Entry Specialist, you turn complex client records into clean, reliable datasets and documents that board members, legal, risk, and compliance teams rely on to make decisions. In this role, you’ll work hands-on with governance data, migrate it between platforms, build smart questionnaires for directors and officers, and use Excel, databases, and AI tools to streamline how information is captured and maintained. You’ll collaborate closely with clients and internal teams, spot data issues early, and suggest better ways of working so implementations run smoothly and clients are set up for long-term success. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Migrate and transform client corporate governance data and documents into Diligent platforms, ensuring accuracy, consistency, and completeness. Build and configure Director & Officer questionnaires so clients can collect the right information from the right stakeholders. Run regular data quality checks, validate data against source records, and quickly correct errors to maintain high data integrity. Use advanced Excel functions, databases, and AI tools to manage, format, and optimize large data sets and bulk document uploads/downloads. Partner directly with client stakeholders and internal teams to clarify requirements, resolve data or technical issues, and provide clear progress updates. Identify and help implement improvements to data workflows, templates, and automation to make delivery faster, more consistent, and more scalable. These are the essentials you’ll need to get an interview Hands-on experience in a data-focused role (for example, data specialist, data analyst, data migration, or similar) in a professional environment. Strong skills in Microsoft Excel, including advanced functions for manipulating and analyzing data

JOB TITLE Data Reliability Engineer A CAREER WITH CUBIST Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures, and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. What you’ll do Ensure smooth day-to-day implementation of a large research infrastructure and the timely delivery of comprehensive and error-free data to Cubist’s portfolio managers across the globe Serve as a frontline owner for mission-critical data ETL pipelines that power trading and investment decision-making, ensuring reliability, accuracy, and timeliness. Actively manage and resolve data incidents in a fast-paced trading environment, partnering closely with investment professionals, data scientists, and external data vendors. Design and build tooling, automation, and robust documentation to improve operational efficiency, scalability, and data quality across the platform. Play a hands-on role in daily data operations, including data validation, remediation, and enrichment, with opportunities to continuously improve and modernize workflows through engineering best practices. What’s REQUIRED Bachelor’s degree in computer science or a related field. Strong proficiency in SQL Server and Python programming, with experience in AWS and both Windows and Linux environments. Exceptional attention to detail with a strong appreciation for well-defined processes and systems. 3+ years of experience in a client-facing support or operations role. Excellent organizational, communication, and interpersonal skills. Commitment to the highest ethical standards About point72 Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Poin

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE We are seeking an experienced MDM Product Data Analyst to support the management, quality, governance, and transformation of product master data across enterprise systems. The role will work closely with Product, Business, Engineering, Data Governance, and technical teams to analyze complex product data, define and validate data quality rules, support MDM onboarding and migration, and drive resolution of data issues. The ideal candidate combines strong product data and MDM expertise with advanced SQL, analytical problem-solving, and practical use of AI/GenAI to improve data analysis and delivery. WHAT YOU'LL DO • Analyze, manage, and reconcile product master data across multiple source systems, MDM platforms, and downstream applications. • Leverage AI/GenAI tools to accelerate data profiling, analysis, data quality rule development, documentation, issue investigation, and root-cause analysis. • Translate business and product requirements into clear data requirements, attribute definitions, validation rules, and analytical specifications. • Perform detailed data profiling to identify quality issues, gaps, inconsistencies, anomalies, duplicates, and data integrity risks across product attributes and relationships. • Define, document, implement, and validate data quality rules covering completeness, accuracy, validity, consistency, uniqueness, and business-rule compliance. • Develop source-to-target analysis and reco

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Smartsheet is looking for an experienced Data Engineer to support and accelerate the productivity of our Go-To Market organization. In this role, you will facilitate Smartsheet's growth strategy through insights produced with data analysis. You will work directly with senior leadership to inform strategic decision-making as part of a collaborative, motivated team. Your work will be instrumental in helping our Sales partners optimize their pipeline, increase retention, and close deals. You Will: Help to create, evolve, and maintain the reporting infrastructure for the Sales organization to promote more intelligent discussion at all stages of the sales funnel. Partner with engineering, data science, and other analytics teams to build scalable analytics solutions with a focus on reporting capabilities. Mine large datasets to ensure data accuracy and completeness for reporting purposes. Analyze and monitor data for anomalies, with a focus on data quality and consistency within reports. Guide commission and territory planning processes with analytical support, providing the necessary reports and data. Develop and maintain key performance indicators (KPIs) to track sales performance, pipeline health, and other critical metrics. Automate report generation and distribution to improve efficiency. Provide technical expertise and guidance to junior analysts on data extraction, transformatio

About Us OpenFX is on a mission to move money as freely as data, unrestricted by time zones, banking hours, or legacy systems. We are building the infrastructure that will power the next generation of cross-border payment systems for institutions. The team's execution has been exceptional, and we're scaling at a remarkable pace. Our stellar early team comes with experience in companies like J.P. Morgan, Goldman Sachs, FalconX, PayPal, Affirm, Polygon, Kraken, Nium & others. We're backed by Accel, Lightspeed, NfX and other top-tier investors. Role Overview OpenFX processes billions of dollars in transaction volume every month across global corridors. Data Engineering owns the pipelines that carry that activity from our trading, banking and settlement systems, and from every bank and liquidity provider we work with, into the lakehouse: ingestion in batch and in real time, the bronze, silver and gold layers that turn raw events into canonical datasets, the orchestration that keeps them fresh, and the quality, governance and cost controls around them. Key Responsibilities Lead and support the Data Engineering pod. You are accountable for the roadmap, the engineering standards and the data platform. You create the conditions in which the team can deliver them. Own ingestion. Bring every source into the lakehouse reliably, whether by batch, streaming or change data capture, from production databases and event streams to the files and APIs of our banking and liquidity partners. Own the lakehouse and its layers: raw data preserved in bronze, cleaned and conformed data in silver, and gold datasets that are modelled, documented and safe to build on. Set the standards for how data moves between them and who owns each layer. Own orchestration and the delivery path for data: scheduled and event-driven pipelines, CI/CD and testing for data code, environments, backfills and schema change. Own data quality and reliability. Define freshness, completeness and accuracy standards f