317 Data Profiling Jobs - Page 13

KDataScience (USA & INDIA) is looking for Senior Data Engineer to join our dynamic team and embark on a rewarding career journey Designing and implementing scalable and reliable data pipelines, data models, and data infrastructure for processing large and complex datasets. Developing and maintaining databases, data warehouses, and data lakes that store and manage the organization's data. Developing and implementing data integration and ETL (Extract, Transform, Load) processes to ensure that data flows smoothly and accurately between different systems and data sources. Ensuring data quality, consistency, and accuracy through data profiling, cleansing, and validation. Building and maintaining data processing and analytics systems that support business intelligence, machine learning, and other data-driven applications. Optimizing the performance and scalability of data systems and infrastructure to ensure that they can handle the organization's growing data needs.

Job Title: Data Engineer – Snowflake & Python About the Role: We are seeking a skilled and proactive Data Developer with 3-5 years of hands-on experience in Snowflake , Python , Streamlit , and SQL , along with expertise in consuming REST APIs and working with modern ETL tools like Matillion, Fivetran etc. The ideal candidate will have a strong foundation in data modeling , data warehousing , and data profiling , and will play a key role in designing and implementing robust data solutions that drive business insights and innovation. Key Responsibilities: Design, develop, and maintain data pipelines and workflows using Snowflake and an ETL tool (e.g., Matillion, dbt, Fivetran, or similar). Develop data applications and dashboards using Python and Streamlit. Create and optimize complex SQL queries for data extraction, transformation, and loading. Integrate REST APIs for data access and process automation. Perform data profiling, quality checks, and troubleshooting to ensure data accuracy and integrity. Design and implement scalable and efficient data models aligned with business requirements. Collaborate with data analysts, data scientists, and business stakeholders to understand data needs and deliver actionable solutions. Implement best practices in data governance, security, and compliance. Required Skills and Qualifications: 3–5 years of professional experience in a data engineering or development role. Strong expertise in Snowflake , including performance tuning and warehouse optimization. Proficient in Python , including data manipulation with libraries like Pandas. Experience building web-based data tools using Streamlit . Solid understanding and experience with RESTful APIs and JSON data structures. Strong SQL skills and experience with advanced data transformation logic. Experience with an ETL tool commonly used with Snowflake (e.g., dbt , Matillion , Fivetran , Airflow ). Hands-on experience in data modeling (dimensional and normalized), data warehousing concepts , and data profiling techniques . Familiarity with version control (e.g., Git) and CI/CD processes is a plus. Preferred Qualifications: Experience working in cloud environments (AWS, Azure, or GCP). Knowledge of data governance and cataloging tools. Experience with agile methodologies and working in cross-functional teams.

Data Analysis & Insights, Retail Data Analytics, Data Processing, Statistical Modeling & Forecasting, Reporting. WhatsApp CV only text +91 8660770495 (no unsch calls pls) Email CV: cv@archangelhr.in, hr@archangelhr.in, hi@archangelhr.in Required Candidate profile B.Tech or equal, with hands-on industry experience in data analysis, R or Python

Job Title: Data Engineer – Snowflake & Python About the Role: We are seeking a skilled and proactive Data Developer with 3-5 years of hands-on experience in Snowflake , Python , Streamlit , and SQL , along with expertise in consuming REST APIs and working with modern ETL tools like Matillion, Fivetran etc. The ideal candidate will have a strong foundation in data modeling , data warehousing , and data profiling , and will play a key role in designing and implementing robust data solutions that drive business insights and innovation. Key Responsibilities: Design, develop, and maintain data pipelines and workflows using Snowflake and an ETL tool (e.g., Matillion, dbt, Fivetran, or similar). Develop data applications and dashboards using Python and Streamlit. Create and optimize complex SQL queries for data extraction, transformation, and loading. Integrate REST APIs for data access and process automation. Perform data profiling, quality checks, and troubleshooting to ensure data accuracy and integrity. Design and implement scalable and efficient data models aligned with business requirements. Collaborate with data analysts, data scientists, and business stakeholders to understand data needs and deliver actionable solutions. Implement best practices in data governance, security, and compliance. Required Skills and Qualifications: Experience in HR Data and databases is a must. 3–5 years of professional experience in a data engineering or development role. Strong expertise in Snowflake , including performance tuning and warehouse optimization. Proficient in Python , including data manipulation with libraries like Pandas. Experience building web-based data tools using Streamlit . Solid understanding and experience with RESTful APIs and JSON data structures. Strong SQL skills and experience with advanced data transformation logic. Experience with an ETL tool commonly used with Snowflake (e.g., dbt , Matillion , Fivetran , Airflow ). Hands-on experience in data modeling (dimensional and normalized), data warehousing concepts , and data profiling techniques . Familiarity with version control (e.g., Git) and CI/CD processes is a plus. Preferred Qualifications: Experience working in cloud environments (AWS, Azure, or GCP). Knowledge of data governance and cataloging tools. Experience with agile methodologies and working in cross-functional teams. Experience in HR Data and databases. Experience in Azure Data Factory

Immediate Job Opening Informatica CDQ Developer (Contract Position) We are hiring Informatica CDQ Professionals with 4 to 8 years of experience for a contract position (6 months to 1 year). This is a Work from Office opportunity based in Mumbai. Job Details: Role: Informatica CDQ Developer Type: Contract (6 months to 1 year) Start Date: Immediate joiners preferred Skills Required: Strong hands-on experience with Informatica Cloud Data Quality (CDQ) Expertise in data profiling, data cleansing, and implementing data quality rules Solid knowledge of data governance and data management Strong troubleshooting and performance optimization skills

We are looking for an experienced SAP Data Migration Specialist who will be responsible for leading the migration process from SAP ECC to SAP S/4HANA. The ideal candidate should have a deep understanding of SAP Data Migration processes, including Data Cleansing, Data Analytics, and Data Profiling, along with the ability to manage a team of professionals across parallel projects. Key Responsibilities: Lead the migration process from SAP ECC to SAP S/4HANA. Oversee data cleansing, transformation, and validation processes. Provide subject matter expertise on SAP Data Migration and guide the team. Execute data cleansing activities and resolve data quality issues. Develop and implement migration strategies to ensure data integrity. Perform data analysis, transformation, and standardization according to S/4HANA requirements. Collaborate with project managers, business users, and technical teams to address data issues. Document and report on data quality, progress, and migration status. Qualifications: Education : Bachelors degree in computer science, Information Systems, or related field. Experience : At least 8 years in SAP Data Migration, including 4 years of hands-on experience with SAP S/4HANA migration. Strong expertise in Data Cleansing, Data Analytics, Data Profiling, and Data Migration tools. Experience with SAP MDG methodology and modules is a plus. Certifications : SAP MDG certification is preferred but not mandatory. Ability to manage multiple projects and meet deadlines. Desired Attributes: Strong communication and collaboration skills. Ability to mentor a team and manage project goals. Detail-oriented with a commitment to data accuracy. 4-6 years of experience in SAP MDM and Data Migration projects. Hands-on exposure to data extraction, cleansing, transformation, validation, and ETL processes. At least 1 year of experience supporting SAP S/4HANA migration. Proficiency in SQL and familiarity with Data Migration tools. Good understanding of data profiling and analytics. Strong communication and collaboration skills.

"Key Responsibilities: Implement scalable data architecture to support enterprise product and analytics needs. Identify opportunities to enhance data platform scalability and reduce cost. Design and develop robust data integration solutions using Data Build Tool (DBT) and other data pipeline tools. Work with complex SQL functions and transform large data sets to meet business requirements. Drive creation and maintenance of data models that support analytics use cases and business objectives. Lead DataOps (CI/CD) initiatives and orchestrate data pipeline jobs to ensure efficient data flow. Collaborate with various stakeholders, including technical teams, functional SMEs, and business users, to understand and address their data needs. Communicate architecture considerations and the impact of technical decisions effectively to a large cross-functional audience. Take ownership of problems, demonstrate a proactive approach to problem-solving, and drive solutions to completion. Required Qualifications: 5+ years of experience in cloud data architecture and analytics. Proficient in Snowflake, SQL, and DBT. Extensive experience in designing and developing data integration solutions using DBT and other data pipeline tools Proven experience in data quality, data profiling and analysis of new data sources. Solid data modelling experience with a business-oriented approach to analytics use cases. Experience with DataOps (CI/CD) and orchestration of data pipeline jobs. Excellent verbal communication skills to articulate architecture considerations and technical decisions. Self-initiated, problem solver with a strong sense of ownership. Preferred Qualifications: Experience in the healthcare or retail industry. Experience with real-time data ingestion. Familiarity with tools such as FiveTran, Ataccama (data quality and observability) with Master Data Management.

ABOUT AMGEN Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today. ABOUT THE ROLE Role Description We are seeking an MDM Associate Data Engineer with 2 –5 years of experience to support and enhance our enterprise MDM (Master Data Management) platforms using Informatica/Reltio. This role is critical in delivering high-quality master data solutions across the organization, utilizing modern tools like Databricks and AWS to drive insights and ensure data reliability. The ideal candidate will have strong SQL, data profiling, and experience working with cross-functional teams in a pharma environment. To succeed in this role, the candidate must have strong data engineering experience along with MDM knowledge, hence the candidates having only MDM experience are not eligible for this role. Candidate must have data engineering experience on technologies like (SQL, Python, PySpark , Databricks, AWS etc ), along with knowledge of MDM (Master Data Management) Roles & Responsibilities Analyze and manage customer master data using Reltio or Informatica MDM solutions. Perform advanced SQL queries and data analysis to validate and ensure master data integrity. Leverage Python, PySpark , and Databricks for scalable data processing and automation. Collaborate with business and data engineering teams for continuous improvement in MDM solutions. Implement data stewardship processes and workflows, including approval and DCR mechanisms. Utilize AWS cloud services for data storage and compute processes related to MDM. Contribute to metadata and data modeling activities. Track and manage data issues using tools such as JIRA and document processes in Confluence. Apply Life Sciences/Pharma industry context to ensure data standards and compliance. Basic Qualifications and Experience Master’s degree with 1 - 3 years of experience in Business, Engineering, IT or related field OR Bachelor’s degree with 2 - 5 years of experience in Business, Engineering, IT or related field OR Diploma with 6 - 8 years of experience in Business, Engineering, IT or related field Functional Skills: Must-Have Skills: Advanced SQL expertise and data wrangling. Strong experience in Python and PySpark for data transformation workflows. Strong e xperience with Databricks and AWS architecture. Must have k nowledge of MDM, data governance, stewardship, and profiling practices. In addition to above, candidates having e xperience with Informatica or Reltio MDM platforms will be preferred . Good-to-Have Skills: Experience with IDQ, data modeling and approval workflow/DCR. Background in Life Sciences/Pharma industries. Familiarity with project tools like JIRA and Confluence. Strong grip on data engineering concepts. Professional Certifications Any ETL certification ( e.g. Informatica) Any Data Analysis certification (SQL, Python, Databricks) Any cloud certification (AWS or AZURE) Soft Skills: Strong analytical abilities to assess and improve master data processes and solutions. Excellent verbal and written communication skills, with the ability to convey complex data concepts clearly to technical and non-technical stakeholders. Effective problem-solving skills to address data-related issues and implement scalable solutions. Ability to work effectively with global, virtual teams EQUAL OPPORTUNITY STATEMENT Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

ABOUT AMGEN Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today. ABOUT THE ROLE Role Description We are seeking an MDM Associate Data Engineer with 2 –5 years of experience to support and enhance our enterprise MDM (Master Data Management) platforms using Informatica/Reltio. This role is critical in delivering high-quality master data solutions across the organization, utilizing modern tools like Databricks and AWS to drive insights and ensure data reliability. The ideal candidate will have strong SQL, data profiling, and experience working with cross-functional teams in a pharma environment. To succeed in this role, the candidate must have strong data engineering experience along with MDM knowledge, hence the candidates having only MDM experience are not eligible for this role. Candidate must have data engineering experience on technologies like (SQL, Python, PySpark , Databricks, AWS etc ), along with knowledge of MDM (Master Data Management) Roles & Responsibilities Analyze and manage customer master data using Reltio or Informatica MDM solutions. Perform advanced SQL queries and data analysis to validate and ensure master data integrity. Leverage Python, PySpark , and Databricks for scalable data processing and automation. Collaborate with business and data engineering teams for continuous improvement in MDM solutions. Implement data stewardship processes and workflows, including approval and DCR mechanisms. Utilize AWS cloud services for data storage and compute processes related to MDM. Contribute to metadata and data modeling activities. Track and manage data issues using tools such as JIRA and document processes in Confluence. Apply Life Sciences/Pharma industry context to ensure data standards and compliance. Basic Qualifications and Experience Master’s degree with 1 - 3 years of experience in Business, Engineering, IT or related field OR Bachelor’s degree with 2 - 5 years of experience in Business, Engineering, IT or related field OR Diploma with 6 - 8 years of experience in Business, Engineering, IT or related field Functional Skills: Must-Have Skills: Advanced SQL expertise and data wrangling. Strong experience in Python and PySpark for data transformation workflows. Strong experience with Databricks and AWS architecture. Must have knowledge of MDM, data governance, stewardship, and profiling practices. In addition to above, candidates having experience with Informatica or Reltio MDM platforms will be preferred. Good-to-Have Skills: Experience with IDQ, data modeling and approval workflow/DCR. Background in Life Sciences/Pharma industries. Familiarity with project tools like JIRA and Confluence. Strong grip on data engineering concepts. Professional Certifications Any ETL certification ( e.g. Informatica) Any Data Analysis certification (SQL, Python, Databricks) Any cloud certification (AWS or AZURE) Soft Skills: Strong analytical abilities to assess and improve master data processes and solutions. Excellent verbal and written communication skills, with the ability to convey complex data concepts clearly to technical and non-technical stakeholders. Effective problem-solving skills to address data-related issues and implement scalable solutions. Ability to work effectively with global, virtual teams EQUAL OPPORTUNITY STATEMENT Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Job Title: Sr Data Engineer – Snowflake & Python About the Role: We are seeking a skilled and proactive Sr Data Developer with 5-8 years of hands-on experience in Snowflake , Python , Streamlit , and SQL , along with expertise in consuming REST APIs and working with modern ETL tools like Matillion, Fivetran etc. The ideal candidate will have a strong foundation in data modeling , data warehousing , and data profiling , and will play a key role in designing and implementing robust data solutions that drive business insights and innovation. Key Responsibilities: Design, develop, and maintain data pipelines and workflows using Snowflake and an ETL tool (e.g., Matillion, dbt, Fivetran, or similar). Develop data applications and dashboards using Python and Streamlit. Create and optimize complex SQL queries for data extraction, transformation, and loading. Integrate REST APIs for data access and process automation. Perform data profiling, quality checks, and troubleshooting to ensure data accuracy and integrity. Design and implement scalable and efficient data models aligned with business requirements. Collaborate with data analysts, data scientists, and business stakeholders to understand data needs and deliver actionable solutions. Implement best practices in data governance, security, and compliance. Required Skills and Qualifications: Experience in HR Data and databases is a must. 5–8 years of professional experience in a data engineering or development role. Strong expertise in Snowflake , including performance tuning and warehouse optimization. Proficient in Python , including data manipulation with libraries like Pandas. Experience building web-based data tools using Streamlit . Solid understanding and experience with RESTful APIs and JSON data structures. Strong SQL skills and experience with advanced data transformation logic. Experience with an ETL tool commonly used with Snowflake (e.g., dbt , Matillion , Fivetran , Airflow ). Hands-on experience in data modeling (dimensional and normalized), data warehousing concepts , and data profiling techniques . Familiarity with version control (e.g., Git) and CI/CD processes is a plus. Preferred Qualifications: Experience working in cloud environments (AWS, Azure, or GCP). Knowledge of data governance and cataloging tools. Experience with agile methodologies and working in cross-functional teams. Experience in HR Data and databases. Experience in Azure Data Factory

Overview Deputy Director - Data Engineering PepsiCo operates in an environment undergoing immense and rapid change. Big-data and digital technologies are driving business transformation that is unlocking new capabilities and business innovations in areas like eCommerce, mobile experiences and IoT. The key to winning in these areas is being able to leverage enterprise data foundations built on PepsiCos global business scale to enable business insights, advanced analytics, and new product development. PepsiCos Data Management and Operations team is tasked with the responsibility of developing quality data collection processes, maintaining the integrity of our data foundations, and enabling business leaders and data scientists across the company to have rapid access to the data they need for decision-making and innovation. What PepsiCo Data Management and Operations does: Maintain a predictable, transparent, global operating rhythm that ensures always-on access to high-quality data for stakeholders across the company. Responsible for day-to-day data collection, transportation, maintenance/curation, and access to the PepsiCo corporate data asset Work cross-functionally across the enterprise to centralize data and standardize it for use by business, data science or other stakeholders. Increase awareness about available data and democratize access to it across the company. As a data engineering lead, you will be the key technical expert overseeing PepsiCo's data product build & operations and drive a strong vision for how data engineering can proactively create a positive impact on the business. You'll be empowered to create & lead a strong team of data engineers who build data pipelines into various source systems, rest data on the PepsiCo Data Lake, and enable exploration and access for analytics, visualization, machine learning, and product development efforts across the company. As a member of the data engineering team, you will help lead the development of very large and complex data applications into public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics. You will work closely with process owners, product owners and business users. You'll be working in a hybrid environment with in-house, on-premises data sources as well as cloud and remote systems. Responsibilities Data engineering lead role for D&Ai data modernization (MDIP) Ideally Candidate must be flexible to work an alternative schedule either on tradition work week from Monday to Friday; or Tuesday to Saturday or Sunday to Thursday depending upon coverage requirements of the job. The can didate can work with immediate supervisor to change the work schedule on rotational basis depending on the product and project requirements. Responsibilities Manage a team of data engineers and data analysts by delegating project responsibilities and managing their flow of work as well as empowering them to realize their full potential. Design, structure and store data into unified data models and link them together to make the data reusable for downstream products. Manage and scale data pipelines from internal and external data sources to support new product launches and drive data quality across data products. Create reusable accelerators and solutions to migrate data from legacy data warehouse platforms such as Teradata to Azure Databricks and Azure SQL. Enable and accelerate standards-based development prioritizing reuse of code, adopt test-driven development, unit testing and test automation with end-to-end observability of data Build and own the automation and monitoring frameworks that captures metrics and operational KPIs for data pipeline quality, performance and cost. Collaborate with internal clients (product teams, sector leads, data science teams) and external partners (SI partners/data providers) to drive solutioning and clarify solution requirements. Evolve the architectural capabilities and maturity of the data platform by engaging with enterprise architects to build and support the right domain architecture for each application following well-architected design standards. Define and manage SLAs for data products and processes running in production. Create documentation for learnings and knowledge transfer to internal associates. Qualifications 12+ years of engineering and data management experience Qualifications 12+ years of overall technology experience that includes at least 5+ years of hands-on software development, data engineering, and systems architecture. 8+ years of experience with Data Lakehouse, Data Warehousing, and Data Analytics tools. 6+ years of experience in SQL optimization and performance tuning on MS SQL Server, Azure SQL or any other popular RDBMS 6+ years of experience in Python/Pyspark/Scala programming on big data platforms like Databricks 4+ years in cloud data engineering experience in Azure or AWS. Fluent with Azure cloud services. Azure Data Engineering certification is a plus. Experience with integration of multi cloud services with on-premises technologies. Experience with data modelling, data warehousing, and building high-volume ETL/ELT pipelines. Experience with data profiling and data quality tools like Great Expectations. Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one business intelligence tool such as Power BI or Tableau Experience with running and scaling applications on the cloud infrastructure and containerized services like Kubernetes. Experience with version control systems like ADO, Github and CI/CD tools for DevOps automation and deployments. Experience with Azure Data Factory, Azure Databricks and Azure Machine learning tools. Experience with Statistical/ML techniques is a plus. Experience with building solutions in the retail or in the supply chain space is a plus. Understanding of metadata management, data lineage, and data glossaries is a plus. BA/BS in Computer Science, Math, Physics, or other technical fields. Candidate must be flexible to work an alternative work schedule either on tradition work week from Monday to Friday; or Tuesday to Saturday or Sunday to Thursday depending upon product and project coverage requirements of the job. Candidates are expected to be in the office at the assigned location at least 3 days a week and the days at work needs to be coordinated with immediate supervisor Skills, Abilities, Knowledge: Excellent communication skills, both verbal and written, along with the ability to influence and demonstrate confidence in communications with senior level management. Proven track record of leading, mentoring data teams. Strong change manager. Comfortable with change, especially that which arises through company growth. Ability to understand and translate business requirements into data and technical requirements. High degree of organization and ability to manage multiple, competing projects and priorities simultaneously. Positive and flexible attitude to enable adjusting to different needs in an ever-changing environment. Strong leadership, organizational and interpersonal skills; comfortable managing trade-offs. Foster a team culture of accountability, communication, and self-management. Proactively drives impact and engagement while bringing others along. Consistently attain/exceed individual and team goals. Ability to lead others without direct authority in a matrixed environment. Comfortable working in a hybrid environment with teams consisting of contractors as well as FTEs spread across multiple PepsiCo locations. Domain Knowledge in CPG industry with Supply chain/GTM background is preferred.

ABOUT AMGEN Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today. ABOUT THE ROLE Role Description We are seeking an MDM Associate Analyst with 2 –5 years of development experience to support and enhance our enterprise MDM (Master Data Management) platforms using Informatica/Reltio. This role is critical in delivering high-quality master data solutions across the organization, utilizing modern tools like Databricks and AWS to drive insights and ensure data reliability. The ideal candidate will have strong SQL, data profiling, and experience working with cross-functional teams in a pharma environment. To succeed in this role, the candidate must have strong experience on MDM (Master Data Management) on configuration (L3 Configuration, Assets creati on, Data modeling etc ) , ETL and data mappings (CAI, CDI ) , data mastering (Match/Merge and Survivorship rules) , source and target integrations ( RestAPI , Batch integration, Integration with Databricks tables etc ) Roles & Responsibilities Analyze and manage customer master data using Reltio or Informatica MDM solutions. Perform advanced SQL queries and data analysis to validate and ensure master data integrity. Leverage Python, PySpark , and Databricks for scalable data processing and automation. Collaborate with business and data engineering teams for continuous improvement in MDM solutions. Implement data stewardship processes and workflows, including approval and DCR mechanisms. Utilize AWS cloud services for data storage and compute processes related to MDM. Contribute to metadata and data modeling activities. Track and manage data issues using tools such as JIRA and document processes in Confluence. Apply Life Sciences/Pharma industry context to ensure data standards and compliance. Basic Qualifications and Experience Master’s degree with 1 - 3 years of experience in Business, Engineering, IT or related field OR Bachelor’s degree with 2 - 5 years of experience in Business, Engineering, IT or related field OR Diploma with 6 - 8 years of experience in Business, Engineering, IT or related field Functional Skills: Must-Have Skills: Strong experience with Informatica or Reltio MDM platforms in building configurations from scratch (Like L3 configuration or Data modeling, Assets creations, Setting up API integrations, Orchestration) Strong experience in building data mappings, data profiling, creating and implementation business rules for data quality and data transformation Strong experience in implementing match and merge rules and survivorship of golden records Expertise in integrating master data records with downstream systems Very good understanding of DWH basics and good knowledge on data modeling Experience with IDQ, data modeling and approval workflow/DCR. Advanced SQL expertise and data wrangling. Exposure to Python and PySpark for data transformation workflows. Knowledge of MDM, data governance, stewardship, and profiling practices. Good-to-Have Skills: Familiarity with Databricks and AWS architecture. Background in Life Sciences/Pharma industries. Familiarity with project tools like JIRA and Confluence. Basics of data engineering concepts. Professional Certifications Any ETL certification ( e.g. Informatica) Any Data Analysis certification (SQL , Python, Databricks ) Any cloud certification (AWS or AZURE) Soft Skills: Strong analytical abilities to assess and improve master data processes and solutions. Excellent verbal and written communication skills, with the ability to convey complex data concepts clearly to technical and non-technical stakeholders. Effective problem-solving skills to address data-related issues and implement scalable solutions. Ability to work effectively with global, virtual teams EQUAL OPPORTUNITY STATEMENT Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

ABOUT AMGEN Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today. ABOUT THE ROLE Role Description We are seeking an MDM Associate Data Steward who will be responsible for ensuring the accuracy, completeness, and reliability of master data across critical business domains such as Customer, Product, Affiliations, and Payer. This role involves actively managing and curating master data through robust data stewardship processes, comprehensive data cataloging, and data governance frameworks utilizing Informatica or Reltio MDM platforms. Additionally, the incumbent will perform advanced data analysis, data validation, and data transformation tasks through SQL queries and Python scripts to enable informed, data-driven business decisions. The role emphasizes cross-functional collaboration with various teams, including Data Engineering, Commercial, Medical, Compliance, and IT, to align data management activities with organizational goals and compliance standards. ? Roles & Responsibilities? ? Responsible for master data stewardship, ensuring data accuracy and integrity across key master data domains (e.g., Customer, Product, Affiliations). Conduct advanced data profiling, cataloging, and reconciliation activities using Informatica or Reltio MDM platforms. Manage the reconciliation of potential matches, ensuring accurate resolution of data discrepancies and preventing duplicate data entries. Effectively manage Data Change Request (DCR) processes, including reviewing, approving, and documenting data updates in compliance with established procedures and SLAs. Execute and optimize SQL queries for validation and analysis of master data. Perform basic Python for data transformation, quality checks, and automation. Collaborate effectively with cross-functional teams including Data Engineering, Commercial, Medical, Compliance, and IT to fulfill data requirements. Support user acceptance testing (UAT) and system integration tests for MDM related system updates. Implement data governance processes ensuring compliance with enterprise standards, policies, and frameworks. Document and maintain accurate SOPs, Data Catalogs, Playbooks, and SLAs. Identify and implement process improvements to enhance data stewardship and analytic capabilities. Perform regular audits and monitoring to maintain high data quality and integrity. Basic Qualifications and Experience? Master’s degree with 1 - 3 years of experience in Business, Engineering, IT or related field? OR ?? Bachelor’s degree with 2 - 5 years of experience in Business, Engineering, IT or related field? OR ? Diploma with 6 - 8 years of experience in Business, Engineering, IT or related field? Functional Skills: ? Must-Have Skills: ? Direct experience in data stewardship, data profiling, and master data management. Hands-on experience with Informatica or Reltio MDM platforms. Proficiency in SQL for data analysis and querying. Knowledge of data cataloging techniques and tools. Basic proficiency in Python scripting for data processing. Good-to-Have Skills: ? Experience with PySpark and Databricks for large-scale data processing. Background in the pharmaceutical, healthcare, or life sciences industries. Familiarity with AWS or other cloud-based data solutions. Strong project management and agile workflow familiarity (e.g., using Jira, Confluence). Understanding of regulatory compliance related to data protection (GDPR, CCPA). Professional Certifications ? Any ETL certification ( e.g. Informatica)? Any Data Analysis certification (SQL)? Any cloud certification (AWS or AZURE)? Soft Skills: Strong analytical abilities to assess and improve master data processes and solutions. Excellent verbal and written communication skills, with the ability to convey complex data concepts clearly to technical and non-technical stakeholders. Effective problem-solving skills to address data-related issues and implement scalable solutions. Ability to work effectively with global, virtual teams EQUAL OPPORTUNITY STATEMENT Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

About The Role eClerx is hiring a Product Data Management Analyst who will work within our Product Data Management team to help our customers enhance online product data quality for Electrical, Mechanical & Electronics products. It will also involve creating technical specifications and product descriptions for online presentation. The candidate will also be working on consultancy projects on redesigning e-commerce customers website taxonomy and navigation. The ideal candidate must possess strong communication skills, with an ability to listen and comprehend information and share it with all the key stakeholders, highlighting opportunities for improvement and concerns, if any. He/she must be able to work collaboratively with teams to execute tasks within defined timeframes while maintaining high-quality standards and superior service levels. The ability to take proactive actions and willingness to take up responsibility beyond the assigned work area is a plus. Apprentice_Analyst Roles and responsibilities: Data enrichment/gap fill, standardization, normalization, and categorization of online and offline product data via research through different sources like internet, specific websites, database, etc. Data quality check and correction Data profiling and reporting (basic) Email communication with the client on request acknowledgment, project status and response on queries Help customers in enhancing their product data quality (electrical, mechanical, electronics) from the technical specification and description perspective Provide technical consulting to the customer category managers around the industry best practices of product data enhancement Technical and Functional Skills: Bachelors Degree in Engineering from Electrical, Mechanical OR Electronics stream Excellent technical knowledge of engineering products (Pumps, motors, HVAC, Plumbing, etc.) and technical specifications Intermediate knowledge of MS Office/Internet.

As Data Engineer at IBM you will harness the power of data to unveil captivating stories and intricate patterns. You’ll contribute to data gathering, storage, and both batch and real-time processing. Collaborating closely with diverse teams, you’ll play an important role in deciding the most suitable data management systems and identifying the crucial data required for insightful analysis. As a Data Engineer, you’ll tackle obstacles related to database integration and untangle complex, unstructured data sets. In this role, your responsibilities may include: Implementing and validating predictive models as well as creating and maintain statistical models with a focus on big data, incorporating a variety of statistical and machine learning techniques Designing and implementing various enterprise search applications such as Elasticsearch and Splunk for client requirements Work in an Agile, collaborative environment, partnering with other scientists, engineers, consultants and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviour’s. Build teams or writing programs to cleanse and integrate data in an efficient and reusable manner, developing predictive or prescriptive models, and evaluating modelling results Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Experience in the integration efforts between Alation and Manta, ensuring seamless data flow and compatibility. Collaborate with cross-functional teams to gather requirements and design solutions that leverage both Alation and Manta platforms effectively. Develop and maintain data governance processes and standards within Alation, leveraging Manta's data lineage capabilities. Analyze data lineage and metadata to provide insights into data quality, compliance, and usage patterns Preferred technical and professional experience Lead the evaluation and implementation of new features and updates for both Alation and Manta platforms Ensuring alignment with organizational goals and objectives. Drive continuous improvement initiatives to enhance the efficiency and effectiveness of data management processes, leveraging Alati

Project Role : Data Engineer Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems. Must have skills : Data Modeling Techniques and Methodologies Project Role Description : Assists with the data platform blueprint and design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models. Must have Skills : Data Modeling Techniques and Methodologies, SSI: NON SSI: Good to Have Skills :SSI: Data Engineering, Cloud Data Migration NON SSI : Job Requirements : Key Responsibilities : 1Drive discussions with clients deal teams to understand business requirements, how Industry Data Model fits in implementation and solutioning 2Develop the solution blueprint and scoping, estimation, staffing for delivery project and solutioning 3Drive Discovery activities and design workshops with client and lead strategic road mapping and operating model design discussions 4Good to have Data Vault,Cloud DB design,Graph data modeling, Ontology, Data Engineering,Data Lake design Technical Experience : 1 7plus year overall exp,3plus Data Modeling,Cloud DB Model,3NF,Dimensional,Conversion of RDBMS data model to Graph Data ModelInstrumental in DB design through all stages of Data Model 2 Exp on at least one Cloud DB Design work must be familiar with Data Architecture Principles Professional Attributes : 1Strong requirement analysis and technical solutioning skill in Data and Analytics 2Excellent writing, communication and presentation skills 3Eagerness to learn and develop self on an ongoing basis 4Excellent client facing and interpersonal skills

Project Role : Data Governance Practitioner Project Role Description : Establish and enforce data governance policies to ensure the accuracy, integrity, and security of organizational data. Collaborate with key stakeholders to define data standards, facilitate effective data collection, storage, access, and usage; and drive data stewardship initiatives for comprehensive and effective data governance. Must have skills : Collibra Data Governance Good to have skills : NA Minimum 3 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Data Governance Practitioner, you will establish and enforce data governance policies to ensure the accuracy, integrity, and security of organizational data. Collaborate with key stakeholders to define data standards, facilitate effective data collection, storage, access, and usage; and drive data stewardship initiatives for comprehensive and effective data governance. Roles & Responsibilities: Expected to perform independently and become an SME. Required active participation/contribution in team discussions. Contribute in providing solutions to work related problems. Develop and implement data governance policies and procedures. Collaborate with stakeholders to define data standards. Facilitate effective data collection, storage, access, and usage. Drive data stewardship initiatives for comprehensive data governance. Ensure compliance with data governance policies and regulations. Professional & Technical Skills: Must To Have Skills: Proficiency in Collibra Data Governance. Strong understanding of data governance principles. Experience in implementing data governance frameworks. Knowledge of data quality management. Familiarity with data privacy regulations. Additional Information: The candidate should have a minimum of 3 years of experience in Collibra Data Governance. This position is based at our Pune office. A 15 years full time education is required. Qualification 15 years full time education