322 Data Ingestion Jobs - Page 9

Dear Candidate, We are hiring a Data Engineering Manager to lead a team building data pipelines, models, and analytics infrastructure. Ideal for experienced engineers who can manage both technical delivery and team growth. Key Responsibilities: Lead development of ETL/ELT pipelines and data platforms Manage data engineers and collaborate with analytics/data science teams Architect systems for data ingestion, quality, and warehousing Define best practices for data architecture, testing, and monitoring Required Skills & Qualifications: Strong experience with big data tools (Spark, Kafka, Airflow) Proficiency in SQL, Python, and cloud data services (e.g., Redshift, BigQuery) Proven leadership and team management in data engineering contexts Bonus: Experience with real-time streaming and ML pipeline integration Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Kandi Srinivasa Delivery Manager Integra Technologies

Responsibilities: * Design, develop & maintain data pipelines using Snowflake, AWS/GCP * Collaborate with cross-functional teams on ETL processes & data modeling

As Lead Data Engineer , you'll design and manage scalable ETL pipelines and clean, structured data flows for real-time retail analytics. You'll work closely with ML engineers and business teams to deliver high-quality, ML-ready datasets. Responsibilities: Develop and optimize large-scale ETL pipelines Design schema-aware data flows and dashboard-ready datasets Manage data pipelines on AWS (S3, Glue, Redshift) Work with transactional and retail data for real-time insights

4+ YOE as a Data Engineer/Scientist, hands-on experience working on Data Warehousing, Data ingestion, Data processing, Data Lakes Must have strong development experience using Python. and SQL, understanding of data orchestration tools like Airflow Required Candidate profile Experience with data extraction techniques - CDC, batch-based, Debezium, Kafka Connect, AWS DMS, queuing/messaging systems - SQS, RabbitMQ, Kinesis, AWS, Data/ML - AWS Glue, MWAA, Athena, Redshift

As Data Engineer at IBM you will harness the power of data to unveil captivating stories and intricate patterns. Youll contribute to data gathering, storage, and both batch and real-time processing. Collaborating closely with diverse teams, youll 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, youll 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 behaviours. 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 Expertise in designing and implementing scalable data warehouse solutions on Snowflake, including schema design, performance tuning, and query optimization. Strong experience in building data ingestion and transformation pipelines using Talend to process structured and unstructured data from various sources. Proficiency in integrating data from cloud platforms into Snowflake using Talend and native Snowflake capabilities. Hands-on experience with dimensional and relational data modelling techniques to support analytics and reporting requirements Preferred technical and professional experience Understanding of optimizing Snowflake workloads, including clustering keys, caching strategies, and query profiling. Ability to implement robust data validation, cleansing, and governance frameworks within ETL processes. Proficiency in SQL and/or Shell scripting for custom transformations and automation tasks

Pyspark Developer Location - Bangalore Experience Level - 5+ years Mandatory Notice Period - Immediate to 30 days Work mode - WFO Domain - Banking Job Description: We are seeking a highly skilled Python & PySpark Developer to join our dynamic team. This position will be responsible for developing and maintaining complex data processing systems using Python and PySpark, ensuring high performance and scalability. Responsibilities: Utilize Python and PySpark to design, develop, and maintain robust data processing pipelines. Ensure these solutions are scalable, efficient, and meet business requirements. Demonstrate strong expertise in handling large datasets using Hadoop, Spark, and other big data technologies . Implement data ingestion strategies to ensure timely and accurate data entry into your systems. Apply GitOps principles to manage infrastructure as code, ensuring consistent and reliable deployment of applications across various environments. Design, implement, and optimize data pipelines that can handle diverse data sources and formats. Ensure these pipelines are efficient, reliable, and capable of scaling to accommodate growing data volumes.

As Data Engineer, you will develop, maintain, evaluate and test big data solutions. You will be involved in the development of data solutions using Spark Framework with Python or Scala on Hadoop and AWS Cloud Data Platform Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise AWS Data Vault 2.0 development mechanism for agile data ingestion, storage and scaling Databricks for complex queries on transformation, aggregation, business logic implementation aggregation, business logic implementation AWS Redshift and Redshift spectrum, for complex queries on transformation, aggregation, business logic implementation DWH Concept on star schema, Materialize view concept. Strong SQL and data manipulation/transformation skills Preferred technical and professional experience Robust and Scalable Cloud Infrastructure End-to-End Data Engineering Pipeline Versatile Programming Capabilities

As a Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs. Your primary responsibilities include: Design, build, optimize and support new and existing data models and ETL processes based on our clients business requirements. Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization. Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Must have 5+ years exp in Big Data -Hadoop Spark -Scala ,Python Hbase, Hive Good to have Aws -S3, athena ,Dynomo DB, Lambda, Jenkins GIT Developed Python and pyspark programs for data analysis. Good working experience with python to develop Custom Framework for generating of rules (just like rules engine). Developed Python code to gather the data from HBase and designs the solution to implement using Pyspark. Apache Spark DataFrames/RDD's were used to apply business transformations and utilized Hive Context objects to perform read/write operations. Preferred technical and professional experience Understanding of Devops. Experience in building scalable end-to-end data ingestion and processing solutions Experience with object-oriented and/or functional programming languages, such as Python, Java and Scala

As a Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs. Your primary responsibilities include: Design, build, optimize and support new and existing data models and ETL processes based on our clients business requirements. Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization. Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Must have 5+ years exp in Big Data -Hadoop Spark -Scala ,Python Hbase, Hive Good to have Aws -S3, athena ,Dynomo DB, Lambda, Jenkins GIT Developed Python and pyspark programs for data analysis. Good working experience with python to develop Custom Framework for generating of rules (just like rules engine). Developed Python code to gather the data from HBase and designs the solution to implement using Pyspark. Apache Spark DataFrames/RDD's were used to apply business transformations and utilized Hive Context objects to perform read/write operations. Preferred technical and professional experience Understanding of Devops. Experience in building scalable end-to-end data ingestion and processing solutions Experience with object-oriented and/or functional programming languages, such as Python, Java and Scala

As a Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs. Your primary responsibilities include: Design, build, optimize and support new and existing data models and ETL processes based on our clients business requirements. Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization. Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Must have 5+ years exp in Big Data -Hadoop Spark -Scala ,Python Hbase, Hive Good to have Aws -S3, athena ,Dynomo DB, Lambda, Jenkins GIT Developed Python and pyspark programs for data analysis. Good working experience with python to develop Custom Framework for generating of rules (just like rules engine). Developed Python code to gather the data from HBase and designs the solution to implement using Pyspark. Apache Spark DataFrames/RDD's were used to apply business transformations and utilized Hive Context objects to perform read/write operations Preferred technical and professional experience Understanding of Devops. Experience in building scalable end-to-end data ingestion and processing solutions Experience with object-oriented and/or functional programming languages, such as Python, Java and Scala

As a Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs. Your primary responsibilities include: Design, build, optimize and support new and existing data models and ETL processes based on our clients business requirements. Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization. Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Must have 5+ years exp in Big Data -Hadoop Spark -Scala ,Python Hbase, Hive Good to have Aws -S3, athena ,Dynomo DB, Lambda, Jenkins GIT Developed Python and pyspark programs for data analysis. Good working experience with python to develop Custom Framework for generating of rules (just like rules engine). Developed Python code to gather the data from HBase and designs the solution to implement using Pyspark. Apache Spark DataFrames/RDD's were used to apply business transformations and utilized Hive Context objects to perform read/write operations Preferred technical and professional experience Understanding of Devops. Experience in building scalable end-to-end data ingestion and processing solutions Experience with object-oriented and/or functional programming languages, such as Python, Java and Scala

A Data Engineer specializing in enterprise data platforms, experienced in building, managing, and optimizing data pipelines for large-scale environments. Having expertise in big data technologies, distributed computing, data ingestion, and transformation frameworks. Proficient in Apache Spark, PySpark, Kafka, and Iceberg tables, and understand how to design and implement scalable, high-performance data processing solutions.What you’ll doAs a Data Engineer – Data Platform Services, responsibilities include: Data Ingestion & Processing Designing and developing data pipelines to migrate workloads from IIAS to Cloudera Data Lake. Implementing streaming and batch data ingestion frameworks using Kafka, Apache Spark (PySpark). Working with IBM CDC and Universal Data Mover to manage data replication and movement. Big Data & Data Lakehouse Management Implementing Apache Iceberg tables for efficient data storage and retrieval. Managing distributed data processing with Cloudera Data Platform (CDP). Ensuring data lineage, cataloging, and governance for compliance with Bank/regulatory policies. Optimization & Performance Tuning Optimizing Spark and PySpark jobs for performance and scalability. Implementing data partitioning, indexing, and caching to enhance query performance. Monitoring and troubleshooting pipeline failures and performance bottlenecks. Security & Compliance Ensuring secure data access, encryption, and masking using Thales CipherTrust. Implementing role-based access controls (RBAC) and data governance policies. Supporting metadata management and data quality initiatives. Collaboration & Automation Working closely with Data Scientists, Analysts, and DevOps teams to integrate data solutions. Automating data workflows using Airflow and implementing CI/CD pipelines with GitLab and Sonatype Nexus. Supporting Denodo-based data virtualization for seamless data access Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise 4-7 years of experience in big data engineering, data integration, and distributed computing. Strong skills in Apache Spark, PySpark, Kafka, SQL, and Cloudera Data Platform (CDP). Proficiency in Python or Scala for data processing. Experience with data pipeline orchestration tools (Apache Airflow, Stonebranch UDM). Understanding of data security, encryption, and compliance frameworks Preferred technical and professional experience Experience in banking or financial services data platforms. Exposure to Denodo for data virtualization and DGraph for graph-based insights. Familiarity with cloud data platforms (AWS, Azure, GCP). Certifications in Cloudera Data Engineering, IBM Data Engineering, or AWS Data Analytics

A Data Engineer specializing in enterprise data platforms, experienced in building, managing, and optimizing data pipelines for large-scale environments. Having expertise in big data technologies, distributed computing, data ingestion, and transformation frameworks. Proficient in Apache Spark, PySpark, Kafka, and Iceberg tables, and understand how to design and implement scalable, high-performance data processing solutions.What you’ll doAs a Data Engineer – Data Platform Services, responsibilities include: Data Ingestion & Processing Designing and developing data pipelines to migrate workloads from IIAS to Cloudera Data Lake. Implementing streaming and batch data ingestion frameworks using Kafka, Apache Spark (PySpark). Working with IBM CDC and Universal Data Mover to manage data replication and movement. Big Data & Data Lakehouse Management Implementing Apache Iceberg tables for efficient data storage and retrieval. Managing distributed data processing with Cloudera Data Platform (CDP). Ensuring data lineage, cataloging, and governance for compliance with Bank/regulatory policies. Optimization & Performance Tuning Optimizing Spark and PySpark jobs for performance and scalability. Implementing data partitioning, indexing, and caching to enhance query performance. Monitoring and troubleshooting pipeline failures and performance bottlenecks. Security & Compliance Ensuring secure data access, encryption, and masking using Thales CipherTrust. Implementing role-based access controls (RBAC) and data governance policies. Supporting metadata management and data quality initiatives. Collaboration & Automation Working closely with Data Scientists, Analysts, and DevOps teams to integrate data solutions. Automating data workflows using Airflow and implementing CI/CD pipelines with GitLab and Sonatype Nexus. Supporting Denodo-based data virtualization for seamless data access Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise 4-7 years of experience in big data engineering, data integration, and distributed computing. Strong skills in Apache Spark, PySpark, Kafka, SQL, and Cloudera Data Platform (CDP). Proficiency in Python or Scala for data processing. Experience with data pipeline orchestration tools (Apache Airflow, Stonebranch UDM). Understanding of data security, encryption, and compliance frameworks Preferred technical and professional experience Experience in banking or financial services data platforms. Exposure to Denodo for data virtualization and DGraph for graph-based insights. Familiarity with cloud data platforms (AWS, Azure, GCP). Certifications in Cloudera Data Engineering, IBM Data Engineering, or AWS Data Analytics

As a Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs. Your primary responsibilities include Design, build, optimize and support new and existing data models and ETL processes based on our clients business requirements. Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization. Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Must have 5+ years exp in Big Data -Hadoop Spark -Scala ,Python Hbase, Hive Good to have Aws -S3, athena ,Dynomo DB, Lambda, Jenkins GIT Developed Python and pyspark programs for data analysis. Good working experience with python to develop Custom Framework for generating of rules (just like rules engine). Developed Python code to gather the data from HBase and designs the solution to implement using Pyspark. Apache Spark DataFrames/RDD's were used to apply business transformations and utilized Hive Context objects to perform read/write operations. Preferred technical and professional experience Understanding of Devops. Experience in building scalable end-to-end data ingestion and processing solutions Experience with object-oriented and/or functional programming languages, such as Python, Java and Scala

So, what’s the role all about? We are looking for a highly driven and technically skilled Software Engineer to lead the integration of various Content Management Systems with AWS Knowledge Hub, enabling advanced Retrieval-Augmented Generation (RAG) search across heterogeneous customer data—without requiring data duplication. This role will also be responsible for expanding the scope of Knowledge Hub to support non-traditional knowledge items and enhance customer self-service capabilities. You will work at the intersection of AI, search infrastructure, and developer experience to make enterprise knowledge instantly accessible, actionable, and AI-ready. How will you make an impact? Integrate CMS with AWS Knowledge Hub to allow seamless RAG-based search across diverse data types—eliminating the need to copy data into Knowledge Hub instances. Extend Knowledge Hub capabilities to ingest and index non-knowledge assets, including structured data, documents, tickets, logs, and other enterprise sources. Build secure, scalable connectors to read directly from customer-maintained indices and data repositories. Enable self-service capabilities for customers to manage content sources using App Flow, Tray.ai, configure ingestion rules, and set up search parameters independently. Collaborate with the NLP/AI team to optimize relevance and performance for RAG search pipelines. Work closely with product and UX teams to design intuitive, powerful experiences around self-service data onboarding and search configuration. Implement data governance, access control, and observability features to ensure enterprise readiness. Have you got what it takes? Proven experience with search infrastructure, RAG pipelines, and LLM-based applications. 2+ Years’ hands-on experience with AWS Knowledge Hub, AppFlow, Tray.ai, or equivalent cloud-based indexing/search platforms. Strong backend development skills (Python, Typescript/NodeJS, .NET/Java) and familiarity with building and consuming REST APIs. Infrastructure as a code (IAAS) service like AWS Cloud formation, CDK knowledge Deep understanding of data ingestion pipelines, index management, and search query optimization. Experience working with unstructured and semi-structured data in real-world enterprise settings. Ability to design for scale, security, and multi-tenant environment. What’s in it for you? Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NICE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NICEr! Enjoy NICE-FLEX! At NICE, we work according to the NICE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere. Reporting into: Tech Manager, Engineering, CX Role Type: Individual Contributor

Immediate Joiners Preferred We're looking for a tech-savvy Consultant experienced in iLevel software , has experience in building/ editing templates for ingestion, data connections, data items (calculated & static) and portal pages , to join a fast-paced team focused on finance and accounts transformation. This is an exciting opportunity for someone who thrives on problem-solving, collaboration, and driving digital efficiencies. Location: Remote Your Future Employer: A global, innovation-driven business solutions provider Responsibilities: 1. Creating dynamic iLevel templates, reports, charts, and graphs for recurring use 2. Enhancing and testing the iLevel Data Model to meet client-specific reporting needs 3. Validating financial models and resolving data/formula breaks efficiently 4. Extracting and formatting data in Excel for recurring portfolio monitoring tasks 5. Collaborating with stakeholders to independently manage multiple iLevel implementation projects Requirements: Minimum 2 years of experience with iLevel software and advanced Excel skills Proficiency in creating iGets and templates for data extraction Exposure to Python, Tableau, and Monday.com is a plus Educational background: B.Com / M.Com / MBA Strong analytical mindset, team player attitude, and proactive communication skills What's in It for You: Competitive compensation and benefits. A chance to work with a global leader and fast-track your career growth through continuous upskilling and innovation-driven projects. Chance to actively contribute to a positive and inclusive team culture. Be part of a fast-growing organization. Reach Us: If you feel this opportunity is well aligned with your career progression plans, please feel free to reach me with your updated profile at vanika.arora@crescendogroup.in for a confidential discussion on role.

Individual Accountabilities Collaboration Collaborates with domain architects in the DSS, OEA, EUS, and HaN towers and if appropriate, the respective business stakeholders in architecting data solutions for their data service needs. Collaborates with the Data Engineering and Data Software Engineering teams to effectively communicate the data architecture to be implemented. Contributes to prototype or proof of concept efforts. Collaborates with InfoSec organization to understand corporate security policies and how they apply to data solutions. Collaborates with the Legal and Data Privacy organization to understand the latest policies so they may be incorporated into every data architecture solution. Suggest architecture design with Ontologies, MDM team. Technical skills & design Significant experience working with structured and unstructured data at scale and comfort with a variety of different stores (key-value, document, columnar, etc.) as well as traditional RDBMS and data warehouses. Deep understanding of modern data services in leading cloud environments, and able to select and assemble data services with maximum cost efficiency while meeting business requirements of speed, continuity, and data integrity. Creates data architecture artifacts such as architecture diagrams, data models, design documents, etc. Guides domain architect on the value of a modern data and analytics platform. Research, design, test, and evaluate new technologies, platforms and third-party products. Working experience with Azure Cloud, Data Mesh, MS Fabric, Ontologies, MDM, IoT, BI solution and AI would be greater assets. Expert troubleshoot skills and experience. Leadership Mentors aspiring data architects typically operating in data engineering and software engineering roles. Key shared accountabilities Leads medium to large data services projects. Provides technical partnership to product owners Shared stewardship, with domains architects, of the Arcadis data ecosystem. Actively participates in Arcadis Tech Architect community. Key profile requirements Minimum of 7 years of experience in designing and implementing modern solutions as part of variety of data ingestion and transformation pipelines Minimum of 5 years of experience with best practice design principles and approaches for a range of application styles and technologies to help guide and steer decisions. Experience working in large scale development and cloud environment.

Who We Are At Kyndryl, we design, build, manage and modernize the mission-critical technology systems that the world depends on every day. So why work at Kyndryl? We are always moving forward – always pushing ourselves to go further in our efforts to build a more equitable, inclusive world for our employees, our customers and our communities. The Role At Kyndryl, we design, build, manage and modernize the mission-critical technology systems that the world depends on every day. So why work at Kyndryl? We are always moving forward – always pushing ourselves to go further in our efforts to build a more equitable, inclusive world for our employees, our customers and our communities. As a Data Engineer , you will leverage your expertise in Databricks , big data platforms , and modern data engineering practices to develop scalable data solutions for our clients. Candidates with healthcare experience, particularly with EPIC systems , are strongly encouraged to apply. This includes creating data pipelines, integrating data from various sources, and implementing data security and privacy measures. The Data Engineer will also be responsible for monitoring and troubleshooting data flows and optimizing data storage and processing for performance and cost efficiency. Responsibilities: Develop data ingestion, data processing and analytical pipelines for big data, relational databases and data warehouse solutions Design and implement data pipelines and ETL/ELT processes using Databricks, Apache Spark, and related tools. Collaborate with business stakeholders, analysts, and data scientists to deliver accessible, high-quality data solutions. Provide guidance on cloud migration strategies and data architecture patterns such as Lakehouse and Data Mesh Provide pros/cons, and migration considerations for private and public cloud architectures Provide technical expertise in troubleshooting, debugging, and resolving complex data and system issues. Create and maintain technical documentation, including system diagrams, deployment procedures, and troubleshooting guides Experience working with Data Governance, Data security and Data Privacy (Unity Catalogue or Purview) If you're ready to embrace the power of data to transform our business and embark on an epic data adventure, then join us at Kyndryl. Together, let's redefine what's possible and unleash your potential. Your Future at Kyndryl Every position at Kyndryl offers a way forward to grow your career. We have opportunities that you won’t find anywhere else, including hands-on experience, learning opportunities, and the chance to certify in all four major platforms. Whether you want to broaden your knowledge base or narrow your scope and specialize in a specific sector, you can find your opportunity here. Who You Are You’re good at what you do and possess the required experience to prove it. However, equally as important – you have a growth mindset; keen to drive your own personal and professional development. You are customer-focused – someone who prioritizes customer success in their work. And finally, you’re open and borderless – naturally inclusive in how you work with others. Required Technical and Professional Experience: 3+ years of consulting or client service delivery experience on Azure Graduate/Postgraduate in computer science, computer engineering, or equivalent with minimum of 8 years of experience in the IT industry. 3+ years of experience in developing data ingestion, data processing and analytical pipelines for big data, relational databases such as SQL server and data warehouse solutions such as Azure Synapse Extensive hands-on experience implementing data ingestion, ETL and data processing. Hands-on experience in and Big Data technologies such as Java, Python, SQL, ADLS/Blob, PySpark and Spark SQL, Databricks, HD Insight and live streaming technologies such as EventHub. Experience with cloud-based database technologies (Azure PAAS DB, AWS RDS and NoSQL). Cloud migration methodologies and processes including tools like Azure Data Factory, Data Migration Service, etc. Experience with monitoring and diagnostic tools (SQL Profiler, Extended Events, etc). Expertise in data mining, data storage and Extract-Transform-Load (ETL) processes. Experience with relational databases and expertise in writing and optimizing T-SQL queries and stored procedures. Experience in using Big Data File Formats and compression techniques. Experience in Developer tools such as Azure DevOps, Visual Studio Team Server, Git, Jenkins, etc. Experience with private and public cloud architectures, pros/cons, and migration considerations. Excellent problem-solving, analytical, and critical thinking skills. Ability to manage multiple projects simultaneously, while maintaining a high level of attention to detail. Communication Skills: Must be able to communicate with both technical and nontechnical. Able to derive technical requirements with the stakeholders. Preferred Technical And Professional Experience Cloud platform certification, e.g., Microsoft Certified: (DP-700) Azure Data Engineer Associate, AWS Certified Data Analytics – Specialty, Elastic Certified Engineer, Google Cloud Professional Data Engineer Professional certification, e.g., Open Certified Technical Specialist with Data Engineering Specialization. Experience working with EPIC healthcare systems (e.g., Clarity, Caboodle). Databricks certifications (e.g., Databricks Certified Data Engineer Associate or Professional). Knowledge of GenAI tools, Microsoft Fabric, or Microsoft Copilot. Familiarity with healthcare data standards and compliance (e.g., HIPAA, GDPR). Experience with DevSecOps and CI/CD deployments Experience in NoSQL databases design Knowledge on , Gen AI fundamentals and industry supporting use cases. Hands-on experience with Delta Lake and Delta Tables within the Databricks environment for building scalable and reliable data pipelines. Being You Diversity is a whole lot more than what we look like or where we come from, it’s how we think and who we are. We welcome people of all cultures, backgrounds, and experiences. But we’re not doing it single-handily: Our Kyndryl Inclusion Networks are only one of many ways we create a workplace where all Kyndryls can find and provide support and advice. This dedication to welcoming everyone into our company means that Kyndryl gives you – and everyone next to you – the ability to bring your whole self to work, individually and collectively, and support the activation of our equitable culture. That’s the Kyndryl Way. What You Can Expect With state-of-the-art resources and Fortune 100 clients, every day is an opportunity to innovate, build new capabilities, new relationships, new processes, and new value. Kyndryl cares about your well-being and prides itself on offering benefits that give you choice, reflect the diversity of our employees and support you and your family through the moments that matter – wherever you are in your life journey. Our employee learning programs give you access to the best learning in the industry to receive certifications, including Microsoft, Google, Amazon, Skillsoft, and many more. Through our company-wide volunteering and giving platform, you can donate, start fundraisers, volunteer, and search over 2 million non-profit organizations. At Kyndryl, we invest heavily in you, we want you to succeed so that together, we will all succeed. Get Referred! If you know someone that works at Kyndryl, when asked ‘How Did You Hear About Us’ during the application process, select ‘Employee Referral’ and enter your contact's Kyndryl email address.

Data Cleansing & Integration Project Delivery: Execute high visibility data programs as assigned by the Data Cleansing Manager. Utilize SAP data load solutions such as SAP Migration Cockpit and LSMW for data loading and template creation. FDO Data Change Management Methodology: Assist in defining data cleansing approaches using Mass Change functionality. Develop and prepare data cleansing strategies. Data Cleansing & Integration Technical Guidance: Understand SAP landscape and data flow to underlying/consumed systems to prevent data synchronization issues. Data Quality: Collaborate with the Data Quality (DQ) team to define DQ rules and enhance visibility of existing data quality. Data Governance: Work with the Data Governance (DG) team to ensure proper governance before implementing system changes. Conduct necessary data load testing in test systems. Data Sourcing: Maintain and update the data catalogue/data dictionary, creating a defined list of data sources indicating the best versions (golden copies). Data Ingestion: Collaborate with DG and project teams on data harmonization by integrating data from multiple sources. Develop sustainable integration routines and methods. Qualifications: Experience: Minimum of 6 years in data-related disciplines such as data management, quality, and cleansing. Technical Skills: Proven experience in delivering data initiatives (cleansing, integration, migrations) using established technical data change methodologies. Proficiency in handling large data sets with tools like Microsoft Excel and Power BI. Experience with SAP native migration and cleansing tools such as SAP Migration Cockpit, LSMW, and MASS. Knowledge of Master Data Management in SAP MDG, SAP ECC, and associated data structures. Collaboration: Ability to work effectively with internal cross-functional teams.

Company: Marsh McLennan Agency Description: Marsh McLennan is seeking candidates for the following position based in the Pune/Mumbai office. Senior Engineer/Principal Engineer What can you expect? We are seeking a skilled Data Engineer with 3 to 5 years of hands-on experience in building and optimizing data pipelines and architectures. The ideal candidate will have expertise in Spark, AWS Glue, AWS S3, Python, complex SQL, and AWS EMR. What is in it for you? Holidays (As Per the location) Medical & Insurance benefits (As Per the location) Shared Transport (Provided the address falls in service zone) Hybrid way of working Diversify your experience and learn new skills Opportunity to work with stakeholders globally to learn and grow We will count on you to: Design and implement scalable data solutions that support our data-driven decision-making processes. What you need to have: SQL and RDBMS knowledge - 5/5. Postgres. Should have extensive hands-on Database systems carrying tables, schema, views, materialized views. AWS Knowledge. Core and Data engineering services. Glue/ Lambda/ EMR/ DMS/ S3 - services in focus. ETL data:dge :- Any ETL tool preferably Informatica. Data warehousing. Big data:- Hadoop - Concepts. Spark - 3/5 Hive - 5/5 Python/ Java. Interpersonal skills:- Excellent communication skills and Team lead capabilities. Understanding of data systems well in big organizations setup. Passion deep diving and working with data and delivering value out of it. What makes you stand out? Databricks knowledge. Any Reporting tool experience. Preferred MicroStrategy. Marsh McLennan (NYSE: MMC) is the worlds leading professional services firm in the areas of risk, strategy and people. The Companys more than 85,000 colleagues advise clients in over 130 countries. With annual revenue of $23 billion, Marsh McLennan helps clients navigate an increasingly dynamic and complex environment through four market-leading businesses. Marsh provides data-driven risk advisory services and insurance solutions to commercial and consumer clients. Guy Carpenter develops advanced risk, reinsurance and capital strategies that help clients grow profitably and pursue emerging opportunities. Mercer delivers advice and technology-driven solutions that help organizations redefine the world of work, reshape retirement and investment outcomes, and unlock health and well being for a changing workforce. Oliver Wyman serves as a critical strategic, economic and brand advisor to private sector and governmental clients. For more information, visit marshmclennan.com, or follow us on LinkedIn and X. Marsh McLennan is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people regardless of their sex/gender, marital or parental status, ethnic origin, nationality, age, background, disability, sexual orientation, caste, gender identity or any other characteristic protected by applicable law. Marsh McLennan is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh McLennan colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one anchor day per week on which their full team will be together in person. Marsh McLennan (NYSE: MMC) is a global leader in risk, strategy and people, advising clients in 130 countries across four businesses: Marsh, Guy Carpenter, Mercer and Oliver Wyman. With annual revenue of $24 billion and more than 90,000 colleagues, Marsh McLennan helps build the confidence to thrive through the power of perspective. For more information, visit marshmclennan.com, or follow on LinkedIn and X. Marsh McLennan is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, caste, disability, ethnic origin, family duties, gender orientation or expression, gender reassignment, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law. Marsh McLennan is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh McLennan colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one anchor day” per week on which their full team will be together in person.

Responsibilities Work with enterprise customers as part of the customer value journey and lead the technical onboarding process of Celonis Lead technical discussions with customers to identify key system architecture components; propose and help customers build solutions that unblock deployments Establish real-time integrations to customer source systems via APIs and Celonis internal integration solutions Advise customers of authentication and user/group management and provisioning solutions for the Celonis platform Eliminate any technical barriers to user adoption of Celonis Develop best practices & blueprints that can be used internally & externally to enable the full Celonis ecosystem Leverage your technical expertise contributing to global programs within the services organization Qualifications A Bachelors (required) or Masters degree (preferred) in Computer Science, Information Systems, Engineering, or a related discipline Solid experience with project management, outstanding customer-centric & proven experience working with customers Experience & interest in working with modern tech stack & methods like REST/SOAP API-Management, Data Ingestion & Streaming, SSO, LDAP, IT Security, Python, Agile, etc. Experience with SQL & Python as well as with data pipelines & ETL processes for large volumes of data Knowledgeable about security and compliance topics for enterprise applications A solution-oriented professional that enjoys deep technical discussions as much as transferring your technical knowledge into understandable terms to a broader audience Experience with at least one of the major cloud platforms (AWS, Azure, GCP) would be a plus Strong communication skills

Who We Are At Kyndryl, we design, build, manage and modernize the mission-critical technology systems that the world depends on every day. So why work at Kyndryl? We are always moving forward – always pushing ourselves to go further in our efforts to build a more equitable, inclusive world for our employees, our customers and our communities. The Role Are you ready to dive headfirst into the captivating world of data engineering at Kyndryl? As a Data Engineer, you'll be the visionary behind our data platforms, crafting them into powerful tools for decision-makers. Your role? Ensuring a treasure trove of pristine, harmonized data is at everyone's fingertips. As a Data Engineer at Kyndryl, you'll be at the forefront of the data revolution, crafting and shaping data platforms that power our organization's success. This role is not just about code and databases; it's about transforming raw data into actionable insights that drive strategic decisions and innovation. In this role, you'll be engineering the backbone of our data infrastructure, ensuring the availability of pristine, refined data sets. With a well-defined methodology, critical thinking, and a rich blend of domain expertise, consulting finesse, and software engineering prowess, you'll be the mastermind of data transformation. Your journey begins by understanding project objectives and requirements from a business perspective, converting this knowledge into a data puzzle. You'll be delving into the depths of information to uncover quality issues and initial insights, setting the stage for data excellence. But it doesn't stop there. You'll be the architect of data pipelines, using your expertise to cleanse, normalize, and transform raw data into the final dataset—a true data alchemist. Armed with a keen eye for detail, you'll scrutinize data solutions, ensuring they align with business and technical requirements. Your work isn't just a means to an end; it's the foundation upon which data-driven decisions are made – and your lifecycle management expertise will ensure our data remains fresh and impactful. So, if you're a technical enthusiast with a passion for data, we invite you to join us in the exhilarating world of data engineering at Kyndryl. Let's transform data into a compelling story of innovation and growth. Your Future at Kyndryl Every position at Kyndryl offers a way forward to grow your career. We have opportunities that you won’t find anywhere else, including hands-on experience, learning opportunities, and the chance to certify in all four major platforms. Whether you want to broaden your knowledge base or narrow your scope and specialize in a specific sector, you can find your opportunity here. Who You Are Who You Are You’re good at what you do and possess the required experience to prove it. However, equally as important – you have a growth mindset; keen to drive your own personal and professional development. You are customer-focused – someone who prioritizes customer success in their work. And finally, you’re open and borderless – naturally inclusive in how you work with others. Required Skills and Experience •Expertise in data mining, data storage and Extract-Transform-Load (ETL) processes •Experience in data pipelines development and tooling, e.g., Glue, Databricks, Synapse, or Dataproc •Experience with both relational and NoSQL databases, PostgreSQL, DB2, MongoDB •Excellent problem-solving, analytical, and critical thinking skills •Ability to manage multiple projects simultaneously, while maintaining a high level of attention to detail •Communication Skills: Must be able to communicate with both technical and non-technical colleagues, to derive technical requirements from business needs and problems Preferred Skills and Experience •Experience working as a Data Engineer and/or in cloud modernization •Experience in Data Modelling, to create conceptual model of how data is connected and how it will be used in business processes •Professional certification, e.g., Open Certified Technical Specialist with Data Engineering Specialization •Cloud platform certification, e.g., AWS Certified Data Analytics– Specialty, Elastic Certified Engineer, Google CloudProfessional Data Engineer, or Microsoft Certified: Azure Data Engineer Associate •Experience working with Kafka , ElasticSearch, Kibana & maintaining data lake •Managing interfaces, monitoring for production deployment including log shipping tool. •Experience in updates, upgrade, patches, VA closure, support with industry best tools •Degree in a scientific discipline, such as Computer Science, Software Engineering, or Information Technology Being You Diversity is a whole lot more than what we look like or where we come from, it’s how we think and who we are. We welcome people of all cultures, backgrounds, and experiences. But we’re not doing it single-handily: Our Kyndryl Inclusion Networks are only one of many ways we create a workplace where all Kyndryls can find and provide support and advice. This dedication to welcoming everyone into our company means that Kyndryl gives you – and everyone next to you – the ability to bring your whole self to work, individually and collectively, and support the activation of our equitable culture. That’s the Kyndryl Way. What You Can Expect With state-of-the-art resources and Fortune 100 clients, every day is an opportunity to innovate, build new capabilities, new relationships, new processes, and new value. Kyndryl cares about your well-being and prides itself on offering benefits that give you choice, reflect the diversity of our employees and support you and your family through the moments that matter – wherever you are in your life journey. Our employee learning programs give you access to the best learning in the industry to receive certifications, including Microsoft, Google, Amazon, Skillsoft, and many more. Through our company-wide volunteering and giving platform, you can donate, start fundraisers, volunteer, and search over 2 million non-profit organizations. At Kyndryl, we invest heavily in you, we want you to succeed so that together, we will all succeed. Get Referred! If you know someone that works at Kyndryl, when asked ‘How Did You Hear About Us’ during the application process, select ‘Employee Referral’ and enter your contact's Kyndryl email address.

esign, implement, and maintain data pipelines for data ingestion, processing, and transformation in Azure. Work together with data scientists and analysts to understand the needs for data and create effective data workflows. Create and maintain data storage solutions including Azure SQL Database, Azure Data Lake, and Azure Blob Storage. Utilizing Azure Data Factory or comparable technologies, create and maintain ETL (Extract, Transform, Load) operations. Implementing data validation and cleansing procedures will ensure the quality, integrity, and dependability of the data. Improve the scalability, efficiency, and cost-effectiveness of data pipelines. Monitoring and resolving data pipeline problems will guarantee consistency and availability of the data. Works in the area of Software Engineering, which encompasses the development, maintenance and optimization of software solutions/applications.1. Applies scientific methods to analyse and solve software engineering problems.2. He/she is responsible for the development and application of software engineering practice and knowledge, in research, design, development and maintenance.3. His/her work requires the exercise of original thought and judgement and the ability to supervise the technical and administrative work of other software engineers.4. The software engineer builds skills and expertise of his/her software engineering discipline to reach standard software engineer skills expectations for the applicable role, as defined in Professional Communities.5. The software engineer collaborates and acts as team player with other software engineers and stakeholders.

Design, implement, and maintain data pipelines for data ingestion, processing, and transformation in Azure. Work together with data scientists and analysts to understand the needs for data and create effective data workflows. Create and maintain data storage solutions including Azure SQL Database, Azure Data Lake, and Azure Blob Storage. Utilizing Azure Data Factory or comparable technologies, create and maintain ETL (Extract, Transform, Load) operations. Implementing data validation and cleansing procedures will ensure the quality, integrity, and dependability of the data. Improve the scalability, efficiency, and cost-effectiveness of data pipelines. Monitoring and resolving data pipeline problems will guarantee consistency and availability of the data. Works in the area of Software Engineering, which encompasses the development, maintenance and optimization of software solutions/applications.1. Applies scientific methods to analyse and solve software engineering problems.2. He/she is responsible for the development and application of software engineering practice and knowledge, in research, design, development and maintenance.3. His/her work requires the exercise of original thought and judgement and the ability to supervise the technical and administrative work of other software engineers.4. The software engineer builds skills and expertise of his/her software engineering discipline to reach standard software engineer skills expectations for the applicable role, as defined in Professional Communities.5. The software engineer collaborates and acts as team player with other software engineers and stakeholders.

As a Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs. Your primary responsibilities include: Design, build, optimize and support new and existing data models and ETL processes based on our clients business requirements. Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization. Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Must have 5+ years exp in Big Data -Hadoop Spark -Scala ,Python Hbase, Hive Good to have Aws -S3, athena ,Dynomo DB, Lambda, Jenkins GIT Developed Python and pyspark programs for data analysis. Good working experience with python to develop Custom Framework for generating of rules (just like rules engine). Developed Python code to gather the data from HBase and designs the solution to implement using Pyspark. Apache Spark DataFrames/RDD's were used to apply business transformations and utilized Hive Context objects to perform read/write operations Preferred technical and professional experience Understanding of Devops. Experience in building scalable end-to-end data ingestion and processing solutions Experience with object-oriented and/or functional programming languages, such as Python, Java and Scala