52 Sparksql Jobs

As a Data Engineer specializing in Pyspark and SQL at Barclays, your main role will involve spearheading the evolution of the digital landscape, driving innovation and excellence within the company. You will be responsible for harnessing cutting-edge technology to revolutionize digital offerings, ensuring unparalleled customer experiences. Working as part of a team of developers, your primary focus will be delivering a technology stack using your strong analytical and problem-solving skills to understand business requirements and deliver quality solutions. Key Responsibilities: - Hands-on experience in Pyspark with a strong knowledge of Dataframes, RDD, and SparkSQL. - Proficiency in Pyspark performance optimization techniques. - Development, testing, and maintenance of applications on AWS Cloud. - Strong grasp of AWS Data Analytics Technology Stack including Glue, S3, Lambda, Lake formation, and Athena. - Design and implementation of scalable and efficient data transformation/storage solutions using open table formats such as DELTA, Iceberg, and Hudi. - Experience in using DBT (Data Build Tool) with snowflake/Athena/Glue for ELT pipeline development. - Proficiency in writing advanced SQL and PL SQL programs. - Building reusable components using Snowflake and AWS Tools/Technology. - Project implementation experience in at least two major projects. - Exposure to data governance or lineage tools like Immuta and Alation. - Knowledge of orchestration tools such as Apache Airflow or Snowflake Tasks. - Familiarity with Ab-initio ETL tool is a plus. Qualifications Required: - Ability to engage with Stakeholders, elicit requirements/user stories, and translate requirements into ETL components. - Understanding of infrastructure setup and the ability to provide solutions individually or with teams. - Good knowledge of Data Marts and Data Warehousing concepts. - Possess good analytical and interpersonal skills. - Implementation of Cloud-based Enterprise data warehouse with multiple data platforms along with Snowflake and NoSQL environment to build data movement strategy. In this role based out of Pune, your main purpose will be to build and maintain systems that collect, store, process, and analyze data such as data pipelines, data warehouses, and data lakes to ensure accuracy, accessibility, and security of all data. As a Data Engineer at Barclays, you will be accountable for: - Building and maintaining data architectures pipelines for durable, complete, and consistent data transfer and processing. - Designing and implementing data warehouses and data lakes that manage appropriate data volumes and velocity while adhering to required security measures. - Developing processing and analysis algorithms suitable for the intended data complexity and volumes. - Collaborating with data scientists to build and deploy machine learning models. As part of your analyst expectations, you will be required to perform activities in a timely manner and to a high standard consistently, driving continuous improvement. You will need in-depth technical knowledge and experience in your area of expertise, leading and supervising a team, guiding and supporting professional development, allocating work requirements, and coordinating team resources. Additionally, you will be expected to embody the Barclays Values of Respect, Integrity, Service, Excellence, and Stewardship, and demonstrate the Barclays Mindset of Empower, Challenge, and Drive.,

What this job involves: JLL, an international real estate management company, is seeking an Data Engineer to join our JLL Technologies Team. We are seeking candidates that are self-starters to work in a diverse and fast-paced environment that can join our Enterprise Data team. We are looking for a candidate that is responsible for designing and developing of data solutions that are strategic for the business using the latest technologies Azure Databricks, Python, PySpark, SparkSQL, Azure functions, Delta Lake, Azure DevOps CI/CD. Responsibilities Design, Architect, and Develop solutions leveraging cloud big data technology to ingest, process and analyze large, disparate data sets to exceed business requirements. Design & develop data management and data persistence solutions for application use cases leveraging relational, non-relational databases and enhancing our data processing capabilities. Develop POCs to influence platform architects, product managers and software engineers to validate solution proposals and migrate. Develop data lake solution to store structured and unstructured data from internal and external sources and provide technical guidance to help migrate colleagues to modern technology platform. Contribute and adhere to CI/CD processes, development best practices and strengthen the discipline in Data Engineering Org. Develop systems that ingest, cleanse and normalize diverse datasets, develop data pipelines from various internal and external sources and build structure for previously unstructured data. Using PySpark and Spark SQL, extract, manipulate, and transform data from various sources, such as databases, data lakes, APIs, and files, to prepare it for analysis and modeling. Build and optimize ETL workflows using Azure Databricks and PySpark. This includes developing efficient data processing pipelines, data validation, error handling, and performance tuning. Perform the unit testing, system integration testing, regression testing and assist with user acceptance testing. Articulates business requirements in a technical solution that can be designed and engineered. Consults with the business to develop documentation and communication materials to ensure accurate usage and interpretation of JLL data. Implement data security best practices, including data encryption, access controls, and compliance with data protection regulations. Ensure data privacy, confidentiality, and integrity throughout the data engineering processes. Performs data analysis required to troubleshoot data related issues and assist in the resolution of data issues. Experience & Education Minimum of 4 years of experience as a data developer using Python, PySpark, Spark Sql, ETL knowledge, SQL Server, ETL Concepts. Bachelors degree in Information Science, Computer Science, Mathematics, Statistics or a quantitative discipline in science, business, or social science. Experience in Azure Cloud Platform, Databricks, Azure storage. Effective written and verbal communication skills, including technical writing. Excellent technical, analytical and organizational skills. Technical Skills & Competencies Experience handling un-structured, semi-structured data, working in a data lake environment, leveraging data streaming and developing data pipelines driven by events/queues Hands on Experience and knowledge on real time/near real time processing and ready to code Hands on Experience in PySpark, Databricks, and Spark Sql. Knowledge on json, Parquet and Other file format and work effectively with them No Sql Databases Knowledge like Hbase, Mongo, Cosmos etc. Preferred Cloud Experience on Azure or AWS Python-spark, Spark Streaming, Azure SQL Server, Cosmos DB/Mongo DB, Azure Event Hubs, Azure Data Lake Storage, Azure Search etc. Team player, Reliable, self-motivated, and self-disciplined individual capable of executing on multiple projects simultaneously within a fast-paced environment working with cross functional teams. What we can do for you: Youll join an entrepreneurial, inclusive culture. One where we succeed together across the desk and around the globe. Where like-minded people work naturally together to achieve great things. Our Total Rewards program reflects our commitment to helping you achieve your ambitions in career, recognition, well-being, benefits and pay. Join us to develop your strengths and enjoy a fulfilling career full of varied experiences. Keep those ambitions in sights and imagine where JLL can take you. Scheduled Weekly Hours: 40

What this job involves: JLL, an international real estate management company, is seeking an Data Engineer to join our JLL Technologies Team. We are seeking candidates that are self-starters to work in a diverse and fast-paced environment that can join our Enterprise Data team. We are looking for a candidate that is responsible for designing and developing of data solutions that are strategic for the business using the latest technologies Azure Databricks, Python, PySpark, SparkSQL, Azure functions, Delta Lake, Azure DevOps CI/CD. Responsibilities Design, Architect, and Develop solutions leveraging cloud big data technology to ingest, process and analyze large, disparate data sets to exceed business requirements. Design & develop data management and data persistence solutions for application use cases leveraging relational, non-relational databases and enhancing our data processing capabilities. Develop POCs to influence platform architects, product managers and software engineers to validate solution proposals and migrate. Develop data lake solution to store structured and unstructured data from internal and external sources and provide technical guidance to help migrate colleagues to modern technology platform. Contribute and adhere to CI/CD processes, development best practices and strengthen the discipline in Data Engineering Org. Develop systems that ingest, cleanse and normalize diverse datasets, develop data pipelines from various internal and external sources and build structure for previously unstructured data. Using PySpark and Spark SQL, extract, manipulate, and transform data from various sources, such as databases, data lakes, APIs, and files, to prepare it for analysis and modeling. Build and optimize ETL workflows using Azure Databricks and PySpark. This includes developing efficient data processing pipelines, data validation, error handling, and performance tuning. Perform the unit testing, system integration testing, regression testing and assist with user acceptance testing. Articulates business requirements in a technical solution that can be designed and engineered. Consults with the business to develop documentation and communication materials to ensure accurate usage and interpretation of JLL data. Implement data security best practices, including data encryption, access controls, and compliance with data protection regulations. Ensure data privacy, confidentiality, and integrity throughout the data engineering processes. Performs data analysis required to troubleshoot data related issues and assist in the resolution of data issues. Experience & Education Minimum of 4 years of experience as a data developer using Python, PySpark, Spark Sql, ETL knowledge, SQL Server, ETL Concepts. Bachelors degree in Information Science, Computer Science, Mathematics, Statistics or a quantitative discipline in science, business, or social science. Experience in Azure Cloud Platform, Databricks, Azure storage. Effective written and verbal communication skills, including technical writing. Excellent technical, analytical and organizational skills. Technical Skills & Competencies Experience handling un-structured, semi-structured data, working in a data lake environment, leveraging data streaming and developing data pipelines driven by events/queues Hands on Experience and knowledge on real time/near real time processing and ready to code Hands on Experience in PySpark, Databricks, and Spark Sql. Knowledge on json, Parquet and Other file format and work effectively with them No Sql Databases Knowledge like Hbase, Mongo, Cosmos etc. Preferred Cloud Experience on Azure or AWS Python-spark, Spark Streaming, Azure SQL Server, Cosmos DB/Mongo DB, Azure Event Hubs, Azure Data Lake Storage, Azure Search etc. Team player, Reliable, self-motivated, and self-disciplined individual capable of executing on multiple projects simultaneously within a fast-paced environment working with cross functional teams. What we can do for you: Youll join an entrepreneurial, inclusive culture. One where we succeed together across the desk and around the globe. Where like-minded people work naturally together to achieve great things. Our Total Rewards program reflects our commitment to helping you achieve your ambitions in career, recognition, well-being, benefits and pay. Join us to develop your strengths and enjoy a fulfilling career full of varied experiences. Keep those ambitions in sights and imagine where JLL can take you. Scheduled Weekly Hours: 40

What this job involves: JLL, an international real estate management company, is seeking an Data Engineer to join our JLL Technologies Team. We are seeking candidates that are self-starters to work in a diverse and fast-paced environment that can join our Enterprise Data team. We are looking for a candidate that is responsible for designing and developing of data solutions that are strategic for the business using the latest technologies Azure Databricks, Python, PySpark, SparkSQL, Azure functions, Delta Lake, Azure DevOps CI/CD. Responsibilities Design, Architect, and Develop solutions leveraging cloud big data technology to ingest, process and analyze large, disparate data sets to exceed business requirements. Design & develop data management and data persistence solutions for application use cases leveraging relational, non-relational databases and enhancing our data processing capabilities. Develop POCs to influence platform architects, product managers and software engineers to validate solution proposals and migrate. Develop data lake solution to store structured and unstructured data from internal and external sources and provide technical guidance to help migrate colleagues to modern technology platform. Contribute and adhere to CI/CD processes, development best practices and strengthen the discipline in Data Engineering Org. Develop systems that ingest, cleanse and normalize diverse datasets, develop data pipelines from various internal and external sources and build structure for previously unstructured data. Using PySpark and Spark SQL, extract, manipulate, and transform data from various sources, such as databases, data lakes, APIs, and files, to prepare it for analysis and modeling. Build and optimize ETL workflows using Azure Databricks and PySpark. This includes developing efficient data processing pipelines, data validation, error handling, and performance tuning. Perform the unit testing, system integration testing, regression testing and assist with user acceptance testing. Articulates business requirements in a technical solution that can be designed and engineered. Consults with the business to develop documentation and communication materials to ensure accurate usage and interpretation of JLL data. Implement data security best practices, including data encryption, access controls, and compliance with data protection regulations. Ensure data privacy, confidentiality, and integrity throughout the data engineering processes. Performs data analysis required to troubleshoot data related issues and assist in the resolution of data issues. Experience & Education Minimum of 4 years of experience as a data developer using Python, PySpark, Spark Sql, ETL knowledge, SQL Server, ETL Concepts. Bachelors degree in Information Science, Computer Science, Mathematics, Statistics or a quantitative discipline in science, business, or social science. Experience in Azure Cloud Platform, Databricks, Azure storage. Effective written and verbal communication skills, including technical writing. Excellent technical, analytical and organizational skills. Technical Skills & Competencies Experience handling un-structured, semi-structured data, working in a data lake environment, leveraging data streaming and developing data pipelines driven by events/queues Hands on Experience and knowledge on real time/near real time processing and ready to code Hands on Experience in PySpark, Databricks, and Spark Sql. Knowledge on json, Parquet and Other file format and work effectively with them No Sql Databases Knowledge like Hbase, Mongo, Cosmos etc. Preferred Cloud Experience on Azure or AWS Python-spark, Spark Streaming, Azure SQL Server, Cosmos DB/Mongo DB, Azure Event Hubs, Azure Data Lake Storage, Azure Search etc. Team player, Reliable, self-motivated, and self-disciplined individual capable of executing on multiple projects simultaneously within a fast-paced environment working with cross functional teams. What we can do for you: Youll join an entrepreneurial, inclusive culture. One where we succeed together across the desk and around the globe. Where like-minded people work naturally together to achieve great things. Our Total Rewards program reflects our commitment to helping you achieve your ambitions in career, recognition, well-being, benefits and pay. Join us to develop your strengths and enjoy a fulfilling career full of varied experiences. Keep those ambitions in sights and imagine where JLL can take you. Scheduled Weekly Hours: 40

What this job involves: JLL, an international real estate management company, is seeking an Data Engineer to join our JLL Technologies Team. We are seeking candidates that are self-starters to work in a diverse and fast-paced environment that can join our Enterprise Data team. We are looking for a candidate that is responsible for designing and developing of data solutions that are strategic for the business using the latest technologies Azure Databricks, Python, PySpark, SparkSQL, Azure functions, Delta Lake, Azure DevOps CI/CD. Responsibilities Develop solutions leveraging cloud big data technology to ingest, process and analyze large, disparate data sets to exceed business requirements. Develop data lake solution to store structured and unstructured data from internal and external sources and provide technical guidance to help migrate colleagues to modern technology platform. Contribute and adhere to CI/CD processes, development best practices and strengthen the discipline in Data Engineering Org. Develop systems that ingest, cleanse and normalize diverse datasets, develop data pipelines from various internal and external sources and build structure for previously unstructured data. Using PySpark and Spark SQL, extract, manipulate, and transform data from various sources, such as databases, data lakes, APIs, and files, to prepare it for analysis and modeling. Perform the unit testing, system integration testing, regression testing and assist with user acceptance testing. Consults with the business to develop documentation and communication materials to ensure accurate usage and interpretation of JLL data. Implement data security best practices, including data encryption, access controls, and compliance with data protection regulations. Ensure data privacy, confidentiality, and integrity throughout the data engineering processes. Performs data analysis required to troubleshoot data related issues and assist in the resolution of data issues. Experience & Education Minimum of 2 years of experience as a data developer using Python, PySpark, Spark Sql, ETL knowledge, SQL Server, ETL Concepts. Bachelors degree in Information Science, Computer Science, Mathematics, Statistics or a quantitative discipline in science, business, or social science. Experience in Azure Cloud Platform, Databricks, Azure storage. Effective written and verbal communication skills, including technical writing. Excellent technical, analytical and organizational skills. Technical Skills & Competencies Experience handling un-structured, semi-structured data, working in a data lake environment, leveraging data streaming and developing data pipelines driven by events/queues Hands on Experience and knowledge on real time/near real time processing and ready to code Hands on Experience in PySpark, Databricks, and Spark Sql. Knowledge on json, Parquet and Other file format and work effectively with them NoSql Databases Knowledge like Hbase, Mongo, Cosmos etc. Preferred Cloud Experience on Azure or AWS Python-spark, Spark Streaming, Azure SQL Server, Cosmos DB/Mongo DB, Azure Event Hubs, Azure Data Lake Storage, Azure Search etc. Team player, Reliable, self-motivated, and self-disciplined individual capable of executing on multiple projects simultaneously within a fast-paced environment working with cross functional teams.

What this job involves: JLL, an international real estate management company, is seeking an Data Engineer to join our JLL Technologies Team. We are seeking candidates that are self-starters to work in a diverse and fast-paced environment that can join our Enterprise Data team. We are looking for a candidate that is responsible for designing and developing of data solutions that are strategic for the business using the latest technologies Azure Databricks, Python, PySpark, SparkSQL, Azure functions, Delta Lake, Azure DevOps CI/CD. Responsibilities Develop solutions leveraging cloud big data technology to ingest, process and analyze large, disparate data sets to exceed business requirements. Develop data lake solution to store structured and unstructured data from internal and external sources and provide technical guidance to help migrate colleagues to modern technology platform. Contribute and adhere to CI/CD processes, development best practices and strengthen the discipline in Data Engineering Org. Develop systems that ingest, cleanse and normalize diverse datasets, develop data pipelines from various internal and external sources and build structure for previously unstructured data. Using PySpark and Spark SQL, extract, manipulate, and transform data from various sources, such as databases, data lakes, APIs, and files, to prepare it for analysis and modeling. Perform the unit testing, system integration testing, regression testing and assist with user acceptance testing. Consults with the business to develop documentation and communication materials to ensure accurate usage and interpretation of JLL data. Implement data security best practices, including data encryption, access controls, and compliance with data protection regulations. Ensure data privacy, confidentiality, and integrity throughout the data engineering processes. Performs data analysis required to troubleshoot data related issues and assist in the resolution of data issues. Experience & Education Minimum of 2 years of experience as a data developer using Python, PySpark, Spark Sql, ETL knowledge, SQL Server, ETL Concepts. Bachelors degree in Information Science, Computer Science, Mathematics, Statistics or a quantitative discipline in science, business, or social science. Experience in Azure Cloud Platform, Databricks, Azure storage. Effective written and verbal communication skills, including technical writing. Excellent technical, analytical and organizational skills. Technical Skills & Competencies Experience handling un-structured, semi-structured data, working in a data lake environment, leveraging data streaming and developing data pipelines driven by events/queues Hands on Experience and knowledge on real time/near real time processing and ready to code Hands on Experience in PySpark, Databricks, and Spark Sql. Knowledge on json, Parquet and Other file format and work effectively with them NoSql Databases Knowledge like Hbase, Mongo, Cosmos etc. Preferred Cloud Experience on Azure or AWS Python-spark, Spark Streaming, Azure SQL Server, Cosmos DB/Mongo DB, Azure Event Hubs, Azure Data Lake Storage, Azure Search etc. Team player, Reliable, self-motivated, and self-disciplined individual capable of executing on multiple projects simultaneously within a fast-paced environment working with cross functional teams.

The position is for a Full Time job with rotational shifts based in Nagpur, Pune, or Bangalore. We are looking to fill 4 positions with candidates who have 5 to 8 years of experience. As an AWS Data Engineer, you will be responsible for leading development activities for the Data engineering team. You will collaborate with other teams such as application management and product delivery, working closely with technical leads, product managers, and support teams. Your role will involve providing guidance to the development, support, and product delivery teams. Additionally, you will lead the implementation of tools and technologies to drive cost-efficient architecture and infrastructure. On the other hand, as an Azure Data Engineer, your responsibilities will include creating and maintaining optimal data pipelines, assembling large, complex data sets that meet business requirements, and identifying opportunities for process improvements and automation. You will develop data tools for analytics and data science teams to optimize product performance and build analytics tools for actionable insights into business metrics. Collaboration with stakeholders from various teams will also be essential to address data-related technical issues and support data infrastructure needs. The ideal candidate for the AWS Data Engineer position should have experience with AWS services like S3, Glue, SNS, SQS, Lambda, Redshift, and RDS. Proficiency in programming, especially in Python, is required, along with strong skills in designing complex SQL queries and optimizing data retrieval. Knowledge of spark, Pyspark, Hadoop, Hive, and spark-Sql is also essential. For the Azure Data Engineer role, candidates should have experience with Azure cloud services and developing Big Data applications using Spark, Hive, Sqoop, Kafka, and Map Reduce. Familiarity with stream-processing systems such as Spark-Streaming and Strom will be advantageous.,

At EY, you'll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of yourself. We're counting on your unique voice and perspective to help EY become even better. Join us and build an exceptional experience for yourself, and a better working world for all. EY's Data n Analytics team is a multi-disciplinary technology team delivering client projects and solutions across Data Management, Visualization, Business Analytics, and Automation, covering a wide range of countries and industry sectors. As an Associate Manager - Data Engineering, your main objective will be to support cloud and on-prem platform analytics and data engineering projects initiated across engagement teams. You will conceptualize, design, develop, deploy, and maintain complex technology solutions to help EY solve business problems for clients. This role involves working closely with technical architects, product and business subject matter experts (SMEs), back-end developers, and other solution architects. Your responsibilities will include evaluating and selecting data warehousing tools for business intelligence, designing, developing, and testing in ETL tool environments, providing technical leadership to a team of developers, coordinating with other technology users, adhering to ETL/Data Warehouse development Best Practices, and being responsible for Data orchestration, ingestion, ETL, and reporting architecture for both on-prem and cloud platforms. To qualify for this role, you must have a minimum of 7 years of total experience with 3+ years in the Data warehousing/Business Intelligence field. You should have hands-on experience in creating and implementing data warehouses on client engagements, knowledge of data architecture, and experience with on-prem to cloud migrations. Skills in Azure database offerings, Azure services, database design, modeling, integration, PySpark, SparkSQL, and business intelligence reporting tools are essential. EY offers an opportunity to work with a team of professionals in a market-leading, multi-disciplinary environment, providing coaching, feedback, opportunities for skill development, and career progression. You will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange, with the freedom and flexibility to handle your role in a way that suits you best. EY exists to build a better working world, creating long-term value for clients, people, and society, and building trust in the capital markets. With diverse teams in over 150 countries, EY provides trust through assurance and helps clients grow, transform, and operate across various services.,

Join us as a Data Engineer responsible for supporting the successful delivery of Location Strategy projects to plan, budget, agreed quality, and governance standards. You'll spearhead the evolution of our digital landscape, driving innovation and excellence. You will harness cutting-edge technology to revolutionize our digital offerings, ensuring unparalleled customer experiences. To be successful as a Data Engineer, you should have experience with: - Hands-on experience in PySpark and strong knowledge of Dataframes, RDD, and SparkSQL. - Hands-on experience in developing, testing, and maintaining applications on AWS Cloud. - Strong hold on AWS Data Analytics Technology Stack (Glue, S3, Lambda, Lake Formation, Athena). - Design and implement scalable and efficient data transformation/storage solutions using Snowflake. - Experience in data ingestion to Snowflake for different storage formats such as Parquet, Iceberg, JSON, CSV, etc. - Experience in using DBT (Data Build Tool) with Snowflake for ELT pipeline development. - Experience in writing advanced SQL and PL SQL programs. - Hands-On Experience for building reusable components using Snowflake and AWS Tools/Technology. - Should have worked on at least two major project implementations. - Exposure to data governance or lineage tools such as Immuta and Alation is an added advantage. - Experience in using Orchestration tools such as Apache Airflow or Snowflake Tasks is an added advantage. - Knowledge of Abinitio ETL tool is a plus. Some other highly valued skills may include: - Ability to engage with stakeholders, elicit requirements/user stories, and translate requirements into ETL components. - Ability to understand the infrastructure setup and provide solutions either individually or working with teams. - Good knowledge of Data Marts and Data Warehousing concepts. - Possess good analytical and interpersonal skills. - Implement Cloud-based Enterprise data warehouse with multiple data platforms along with Snowflake and NoSQL environment to build data movement strategy. You may be assessed on key critical skills relevant for success in the role, such as risk and controls, change and transformation, business acumen, strategic thinking, digital and technology, as well as job-specific technical skills. The role is based out of Chennai. Purpose of the role: To build and maintain the systems that collect, store, process, and analyze data, such as data pipelines, data warehouses, and data lakes to ensure that all data is accurate, accessible, and secure. Accountabilities: - Build and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete, and consistent data. - Design and implementation of data warehouses and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures. - Development of processing and analysis algorithms fit for the intended data complexity and volumes. - Collaboration with data scientists to build and deploy machine learning models. Analyst Expectations: To perform prescribed activities in a timely manner and to a high standard consistently driving continuous improvement. Requires in-depth technical knowledge and experience in their assigned area of expertise. Thorough understanding of the underlying principles and concepts within the area of expertise. They lead and supervise a team, guiding and supporting professional development, allocating work requirements, and coordinating team resources. If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviors to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviors are: L Listen and be authentic, E Energize and inspire, A Align across the enterprise, D Develop others. OR for an individual contributor, they develop technical expertise in the work area, acting as an advisor where appropriate. Will have an impact on the work of related teams within the area. Partner with other functions and business areas. Takes responsibility for the end results of a team's operational processing and activities. Escalate breaches of policies/procedures appropriately. Take responsibility for embedding new policies/procedures adopted due to risk mitigation. Advise and influence decision-making within the own area of expertise. Take ownership of managing risk and strengthening controls in relation to the work you own or contribute to. Deliver your work and areas of responsibility following relevant rules, regulations, and codes of conduct. Maintain and continually build an understanding of how your sub-function integrates with the function, alongside knowledge of the organization's products, services, and processes within the function. Demonstrate understanding of how areas coordinate and contribute to the achievement of the objectives of the organization sub-function. Resolve problems by identifying and selecting solutions through the application of acquired technical experience and guided by precedents. Guide and persuade team members and communicate complex/sensitive information. Act as a contact point for stakeholders outside of the immediate function, while building a network of contacts outside the team and external to the organization. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence, and Stewardship our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset to Empower, Challenge, and Drive the operating manual for how we behave.,

The ideal candidate for this role should have a minimum of 5+ years of experience in designing Azure data lakes using tools such as Databricks, PySpark, and SparkSQL. Additionally, the candidate should possess hands-on experience working with Azure SQL Server and other Azure services like Function App, Event Hub, and Encryption/Decryption mechanisms. The successful candidate should have a proven track record of working on large and cutting-edge projects, leading cloud transformation initiatives, and managing operations effectively. They will be responsible for owning the technical architecture and providing guidance to clients on the direction of their projects. Key responsibilities will include deploying solutions across the Azure platform for enterprise projects, creating high-quality documentation for internal teams, and acting as a thought leader in promoting DevOps practices within the organization. The candidate will also be involved in assisting development teams in building CI/CD pipelines, solving complex problems, and offering expert technical advice. This position is based in Chennai, Pune, Bangalore, Noida, or Trichy, and offers an exciting opportunity to work on innovative projects in a dynamic environment.,

Genpact is a global professional services and solutions firm with over 125,000 employees in 30+ countries, driven by curiosity, agility, and a commitment to creating value for clients. We serve leading enterprises worldwide, leveraging our expertise in digital operations, data, technology, and AI. We are seeking a Lead Consultant- Databricks Developer to solve cutting-edge problems and meet functional and non-functional requirements. As a Databricks Developer, you will work closely with architects and lead engineers to design solutions and stay abreast of industry trends and standards. Responsibilities: - Stay updated on new technologies for potential application in service offerings. - Collaborate with architects and lead engineers to develop solutions. - Demonstrate knowledge of industry trends and standards. - Exhibit strong analytical and technical problem-solving skills. - Required experience in the Data Engineering domain. Minimum qualifications: - Bachelor's Degree in CS, CE, CIS, IS, MIS, or equivalent work experience. - Proficiency in Python or Scala, preferably Python. - Experience in Data Engineering with a focus on Databricks. - Implementation of at least 2 projects end-to-end in Databricks. - Proficiency in Databricks components like Delta lake, dbConnect, db API 2.0, and Databricks workflows orchestration. - Understanding of Databricks Lakehouse concept and its implementation. - Ability to create complex data pipelines and knowledge of data structure & algorithms. - Strong skills in SQL and spark-sql. - Experience in performance optimization and working on both batch and streaming data pipelines. - Extensive knowledge of Spark and Hive data processing framework. - Familiarity with cloud platforms like Azure, AWS, GCP, and related services. - Experience in writing unit and integration test cases. - Excellent communication skills and team collaboration experience. Preferred qualifications: - Knowledge of Unity catalog and basic governance. - Understanding of Databricks SQL Endpoint. - Experience with CI/CD for building Databricks job pipelines. - Exposure to migration projects for building Unified data platforms. - Familiarity with DBT, docker, and Kubernetes. Join us as a Lead Consultant in Hyderabad, India, on a full-time basis to contribute to our digital initiatives and shape the future of professional services.,

At Capgemini Invent, we believe in the power of diversity to drive change. As inventive transformation consultants, we leverage our strategic, creative, and scientific capabilities to collaborate closely with clients in delivering cutting-edge solutions. Join our team to lead transformation initiatives tailored to address both current challenges and future opportunities. Our approach is informed and validated by science and data, supercharged by creativity and design, and supported by purpose-driven technology. We are seeking a candidate with strong expertise in SSAS Tabular Model, proficient in DAX queries and query optimization, adept at resolving performance issues, database tuning, and data replication techniques using Microsoft SQL Server. The ideal candidate will have a solid background in working with Stored Procedures, Functions, Triggers, Views, and Data Warehousing, demonstrating clear understanding of concepts such as creating Facts and dimensions. The role requires significant experience in Azure SQL Database, Azure Data Factory (ADF), Azure Databricks (ADB), Azure Synapse, T-SQL, Azure SQL Data Warehouse (DWH), Azure Data Lake Storage (ADLS), SparkSQL/PySpark, and other Azure services for database management, storage, security, and development of Business Intelligence solutions. Familiarity with Microsoft Fabric is considered beneficial, along with proficiency in writing ADB/Synapse notebooks. Additionally, familiarity with Azure functions, Azure Streaming Analytics, Document DB (or Cosmos), MDS (SQL Master Data Service), and Graph DB is preferred. The successful candidate should possess excellent skills in Business Intelligence, problem-solving, analytics, reporting, and visualization. Strong communication skills are essential, as the role involves direct interaction with clients as an individual contributor. Capgemini is a global leader in business and technology transformation, supporting organizations in accelerating their digital and sustainable transition while delivering tangible impact for enterprises and society. With a team of over 340,000 professionals in more than 50 countries, Capgemini leverages its 55-year heritage to unlock the value of technology for its clients, offering end-to-end services and solutions spanning from strategy and design to engineering. The organization's capabilities in AI, cloud, and data, coupled with deep industry expertise and a strong partner ecosystem, enable it to address diverse business needs effectively. In 2023, the Group reported global revenues of 22.5 billion.,

At EY, you'll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of you. And we're counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself and a better working world for all. EY's Data n Analytics team is a multi-disciplinary technology team delivering client projects and solutions across Data Management, Visualization, Business Analytics, and Automation. The assignments cover a wide range of countries and industry sectors. We're looking for a Manager - Data Engineering. The main objective of the role is to support cloud and on-prem platform analytics and data engineering projects initiated across engagement teams. The role will primarily involve conceptualizing, designing, developing, deploying, and maintaining complex technology solutions which help EY solve business problems for the clients. This role will work closely with technical architects, product and business subject matter experts (SMEs), back-end developers, and other solution architects and is also on-shore facing. This role will be instrumental in designing, developing, and evolving the modern data warehousing solutions and data integration build-outs using cutting-edge tools and platforms for both on-prem and cloud architectures. In this role, you will be coming up with design specifications, documentation, and development of data migration mappings and transformations for a modern Data Warehouse set up/data mart creation and define robust ETL processing to collect and scrub both structured and unstructured data providing self-serve capabilities (OLAP) in order to create impactful decision analytics reporting. Your key responsibilities include evaluating and selecting data warehousing tools for business intelligence, data population, data management, metadata management, and warehouse administration for both on-prem and cloud-based engagements. You should have a strong working knowledge across the technology stack including ETL, ELT, data analysis, metadata, data quality, audit, and design. Experience in design documentation, providing technical leadership to a team of data warehouse and business intelligence developers, coordinating with other technology users, and adhering to ETL/Data Warehouse development Best Practices is essential. To qualify for the role, you must have a Bachelor's or equivalent degree in computer science, or a related field, required. An advanced degree or equivalent business experience is preferred. You should be fact-driven and analytically minded with excellent attention to details and have relevant work experience of minimum 9 to 11 years in a big 4 or technology/consulting setup. Ideally, you'll also have the ability to think strategically/end-to-end with a result-oriented mindset, build rapport within the firm and win the trust of the clients, willingness to travel extensively and to work on client sites/practice office locations, and experience with Snowflake. What we look for in candidates is a team of people with commercial acumen, technical experience, and enthusiasm to learn new things in this fast-moving environment. An opportunity to be a part of a market-leading, multi-disciplinary team of 1400+ professionals, in the only integrated global transaction business worldwide. Opportunities to work with EY SaT practices globally with leading businesses across a range of industries. Working at EY offers support, coaching, and feedback from some of the most engaging colleagues around, opportunities to develop new skills and progress your career, the freedom and flexibility to handle your role in a way that's right for you. EY exists to build a better working world, helping to create long-term value for clients, people, and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform, and operate. Working across assurance, consulting, law, strategy, tax, and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.,

You will be working as a full-time on-site Databricks Developer in Hyderabad. Your responsibilities will include designing, developing, and maintaining highly scalable efficient data pipelines using Databricks, PySpark, and other related technologies to process large-scale datasets. Collaboration with cross-functional teams to design and implement data engineering and analytics solutions will be a key part of your role. To excel in this role, you should have expertise in using Unity Catalog and Metastore, optimizing Databricks notebooks, delta lake, and DLT pipelines. You should also be experienced in using Databricks SQL, implementing highly configured data processing solutions, and solutions for data quality and reconciliation requirements. A solid understanding of data governance frameworks, policies, and best practices for data management, security, and compliance is essential. Additionally, you should have a strong knowledge of data modelling techniques and be proficient in PySpark or SparkSQL.,

As a Senior Azure Data Engineer, your responsibilities will include: Building scalable data pipelines using Databricks and PySpark Transforming raw data into usable business insights Integrating Azure services like Blob Storage, Data Lake, and Synapse Analytics Deploying and maintaining machine learning models using MLlib or TensorFlow Executing large-scale Spark jobs with performance tuning on Spark Pools Leveraging Databricks Notebooks and managing workflows with MLflow Qualifications: Bachelors/Masters in Computer Science, Data Science, or equivalent 7+ years in Data Engineering, with 3+ years in Azure Databricks Strong hands-on in: PySpark, Spark SQL, RDDs, Pandas, NumPy, Delta Lake Azure ecosystem: Data Lake, Blob Storage, Synapse Analytics

You should hold a Bachelors or higher degree in Computer Science or a related discipline, or possess equivalent qualifications with a minimum of 4+ years of work experience. Additionally, you should have at least 1+ years of consulting or client service delivery experience specifically related to Azure Microsoft Fabric. Your role will involve 1+ years of experience in developing data ingestion, data processing, and analytical pipelines for big data. This includes working with relational databases like SQL server and data warehouse solutions such as Synapse/Azure Databricks. You must have hands-on experience in implementing data ingestion, ETL, and data processing using various Azure services such as ADLS, Azure Data Factory, Azure Functions, and services in Microsoft Fabric. A minimum of 1+ years of hands-on experience in Azure and Big Data technologies is essential. This includes proficiency in Java, Python, SQL, ADLS/Blob, pyspark/SparkSQL, and Databricks. Moreover, you should have a minimum of 1+ years of experience in working with RDBMS, as well as familiarity with Big Data File Formats and compression techniques. Your expertise should also extend to using Developer tools like Azure DevOps, Visual Studio Team Server, Git, etc. This comprehensive skill set will enable you to excel in this role and contribute effectively to the team.,

You are a PySpark Developer with 3-8 years of experience and have expertise in Apache Spark, Big Data Hadoop Ecosystem, SparkSQL, and Python. Your professional background includes working with Bigdata technologies like PySpark, HIVE, Hadoop, and PLSQL. You also possess a good understanding of AWS, Snowflake, CICD, and system design. It would be advantageous if you have prior experience in Fund transfer AML technologies. Strong communication skills, both written and verbal, are essential for this role. As a self-starter, you should have quick learning abilities and the capability to multitask effectively, even under stringent deadlines. You must be adept at understanding and working on various internal systems while collaborating with multiple stakeholders. If you meet these requirements and are interested in the role, please share your updated resume with preethi.r@ltimindtree.com.,

The role of Scala Spark Developer requires 3-8 years of experience and can be based in Chennai or Pune with any notice period. As a Scala Spark Developer, you will need to have expertise in Apache Spark, Big Data Hadoop Ecosystem, SparkSQL, and Scala. You should possess a minimum of 5 years of Scala+Spark experience, demonstrating hands-on experience in designing and developing big data platforms. Your responsibilities will include working on data engineering projects, utilizing modern data processing technology stacks such as Spark, HBase, Hive, and other Hadoop ecosystem technologies. You will be expected to have a deep understanding of streaming data architectures for real-time and low-latency data processing. Experience with agile development methods and Continuous Integration/Delivery will be beneficial for this role. Knowledge of NoSQL technologies like column family, graph, document, and key-value data storage technologies is a plus. A passion for software craftsmanship and experience in the Financial Industry will also be advantageous. Essential requirements include hands-on experience with Spark and Spark Streaming, in-depth understanding of Spark internals, Spark configuration, Spark memory management, Scala, and Databricks. If you meet the qualifications and are interested in this opportunity, please share your updated resume with preethi.r@ltimindtree.com.,

MongoDB's mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. We enable organizations of all sizes to easily build, scale, and run modern applications by helping them modernize legacy workloads, embrace innovation, and unleash AI. Our industry-leading developer data platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available in more than 115 regions across AWS, Google Cloud, and Microsoft Azure. Atlas allows customers to build and run applications anywhereon premises, or across cloud providers. With offices worldwide and over 175,000 new developers signing up to use MongoDB every month, it's no wonder that leading organizations, like Samsung and Toyota, trust MongoDB to build next-generation, AI-powered applications. As a Senior Analytics Engineer at MongoDB, you will play a critical role in leveraging data to drive informed decision-making and simplify end user engagement across our most critical data sets. You will be responsible for designing, developing, and maintaining robust analytics solutions, ensuring data integrity, and enabling data-driven insights across all of MongoDB. This role requires an analytical thinker with strong technical expertise to contribute to the growth and success of the entire business. This role can be based out of Gurugram. Responsibilities - Design, implement, and maintain highly performant data post-processing pipelines - Create shared data assets that will act as the company's source-of-truth for critical business metrics - Partner with analytics stakeholders to curate analysis-ready datasets and augment the generation of actionable insights - Partner with data engineering to expose governed datasets to the rest of the organization - Make impactful contributions to our analytics infrastructure, systems, and tools - Create and manage documentation, and conduct knowledge sharing sessions to proliferate tribal knowledge and best practices - Maintain consistent planning and tracking of work in JIRA tickets Skills & Attributes - Bachelor's degree (or equivalent) in mathematics, computer science, information technology, engineering, or related discipline - 3-5 years of relevant experience - Strong Proficiency in SQL and experience working with relational databases - Solid understanding of data modeling and ETL processes - Proficiency in Python for automation, data manipulation, and analysis - Experience managing ETL and data pipeline orchestration with dbt and Airflow - Comfortable with command line functions - Familiarity with Hive, Trino (Presto), SparkSQL, Google BigQuery - Experience with cloud data storage like AWS S3, GCS - Experience with managing codebases with git - Consistently employs CI/CD best practices - Experience translating project requirements into a set of technical sub-tasks that build towards a final deliverable - Experience combining data from disparate data sources to identify insights that were previously unknown - Previous project work requiring expertise in business metrics and datasets - Strong communication skills to document technical processes clearly and lead knowledge-sharing efforts across teams - The ability to effectively collaborate cross-functionally to drive actionable and measurable results - Committed to continuous improvement, with a passion for building processes/tools to make everyone more efficient - A passion for AI as an enhancing tool to improve workflows, increase productivity, and generate smarter outcomes - A desire to constantly learn and improve themselves At MongoDB, we're committed to developing a supportive and enriching culture for everyone to drive personal growth and business impact. From employee affinity groups to fertility assistance and a generous parental leave policy, we value our employees" wellbeing and want to support them along every step of their professional and personal journeys. MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter. MongoDB is an equal opportunities employer.,

As a Software Developer at our organization, you will be responsible for independently designing components, developing code, and testing case scenarios using Talend on Big Data while adhering to relevant software craftsmanship principles and meeting acceptance criteria. Your role will also involve completing the assigned learning path, participating in team ceremonies such as agile practices, and delivering on all aspects of the Software Development Lifecycle (SDLC) in-line with Agile and IT craftsmanship principles. You will be expected to deliver high-quality clean code and designs that can be re-used, collaborate with other development teams to define and implement data pipelines, and ensure timely communication with counterparts, stakeholders, and partners. Additionally, you will assess production improvement areas, manage and address production loads, and provide suggestions for automating repetitive production activities. Your responsibilities will also include performing bug-free release validations, producing metrics, tests, and defect reports, assisting in developing guidelines, and increasing the coverage of data models, data dictionary, data pipeline standards, and the storage of source, process, and consumer metadata. Strong communication skills and an understanding of the Agile/Scrum development cycle are essential for this role. To be successful in this position, you should have 4 to 5 years of experience in Databricks, Data Factory, ADF, ADB, Hive, PySpark, SparkSQL, DataLake, DataLakeHouse, deltalake, Azure SQL, Logic Apps, KeyValut, Log Analytics and Metrics, ETL & ELT concepts. Hands-on experience with Azure DevOps and an understanding of build and release pipelines will be advantageous. You should be able to extract data from source systems using Data Factory pipelines and workflows in Azure Data Bricks, and have knowledge of error handling and root cause analysis. Furthermore, you are expected to standardize integration and migration flows, develop scalable and reusable frameworks for ingesting and enhancing datasets, possess good analytical and troubleshooting skills, ensure data quality and accuracy through testing and validation, and work effectively in a team with a cross-cultural environment. Effective verbal and written communication skills are crucial for collaborating with all counterparties. If you are looking for a stimulating and caring environment where you can make a positive impact on the future and grow both personally and professionally, we welcome you to join our team. At our organization, we value diversity and inclusion, and we believe that everyone's initiatives play a significant role in shaping the world of tomorrow.,

Join us as a Data Engineer responsible for supporting the successful delivery of Location Strategy projects to plan, budget, agreed quality and governance standards. You'll spearhead the evolution of our digital landscape, driving innovation and excellence. You will harness cutting-edge technology to revolutionise our digital offerings, ensuring unparalleled customer experiences. To be successful as a Data Engineer, you should have experience with hands-on experience in pyspark and strong knowledge of Dataframes, RDD, and SparkSQL. Additionally, experience in developing, testing, and maintaining applications on AWS Cloud is crucial. A strong hold on the AWS Data Analytics Technology Stack (Glue, S3, Lambda, Lake formation, Athena) is essential. Designing and implementing scalable and efficient data transformation/storage solutions using Snowflake, as well as data ingestion to Snowflake for different storage formats such as Parquet, Iceberg, JSON, CSV, etc., are key requirements. Experience in using DBT (Data Build Tool) with Snowflake for ELT pipeline development and writing advanced SQL and PL SQL programs is necessary. Moreover, hands-on experience in building reusable components using Snowflake and AWS Tools/Technology is expected. Exposure to data governance or lineage tools such as Immuta and Alation, as well as experience in using Orchestration tools such as Apache Airflow or Snowflake Tasks, are considered advantageous. Knowledge of the Abinitio ETL tool is a plus. Some other highly valued skills may include the ability to engage with stakeholders, elicit requirements/user stories, and translate requirements into ETL components. Understanding the infrastructure setup and providing solutions either individually or working with teams is important. Good knowledge of Data Marts and Data Warehousing concepts, possessing good analytical and interpersonal skills, and implementing Cloud-based Enterprise data warehouse with multiple data platforms along with Snowflake and NoSQL environment to build a data movement strategy are also valued skills. The role is based out of Chennai. Purpose of the role: To build and maintain the systems that collect, store, process, and analyze data, such as data pipelines, data warehouses, and data lakes to ensure that all data is accurate, accessible, and secure. Accountabilities: Build and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete, and consistent data. Design and implementation of data warehouses and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures. Development of processing and analysis algorithms fit for the intended data complexity and volumes. Collaboration with data scientists to build and deploy machine learning models. Analyst Expectations: To perform prescribed activities in a timely manner and to a high standard consistently driving continuous improvement. Requires in-depth technical knowledge and experience in their assigned area of expertise. They lead and supervise a team, guiding and supporting professional development, allocating work requirements, and coordinating team resources. If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviors to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviors are: L Listen and be authentic, E Energize and inspire, A Align across the enterprise, D Develop others. OR for an individual contributor, they develop technical expertise in the work area, acting as an advisor where appropriate. Will have an impact on the work of related teams within the area. Partner with other functions and business areas. Takes responsibility for the end results of a team's operational processing and activities. Escalate breaches of policies/procedure appropriately. Take responsibility for embedding new policies/procedures adopted due to risk mitigation. Advise and influence decision-making within their area of expertise. Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to. Deliver your work and areas of responsibility in line with relevant rules, regulation, and codes of conduct. Maintain and continually build an understanding of how your sub-function integrates with function, alongside knowledge of the organization's products, services, and processes within the function. Demonstrate understanding of how areas coordinate and contribute to the achievement of the objectives of the organization sub-function. Resolve problems by identifying and selecting solutions through the application of acquired technical experience and will be guided by precedents. Guide and persuade team members and communicate complex/sensitive information. Act as a contact point for stakeholders outside of the immediate function, while building a network of contacts outside the team and external to the organization. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence, and Stewardship our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset to Empower, Challenge, and Drive the operating manual for how we behave.,

About the job: At Citi, we're not just building technology, we're building the future of banking. Encompassing a broad range of specialties, roles, and cultures, our teams are creating innovations used across the globe. Citi is constantly growing and progressing through our technology, with a laser focus on evolving the ways of doing things. As one of the world's most global banks, we're changing how the world does business. Shape your Career with Citi We're currently looking for a high-caliber professional to join our team as AVP- Data Engineer based in Pune, India. Being part of our team means that we'll provide you with the resources to meet your unique needs, empower you to make healthy decisions, and manage your financial well-being to help plan for your future. For instance: - We provide programs and services for your physical and mental well-being, including access to telehealth options, health advocates, confidential counseling, and more. Coverage varies by country. - We empower our employees to manage their financial well-being and help them plan for the future. - We provide access to an array of learning and development resources to help broaden and deepen your skills and knowledge as your career progresses. In this role, you're expected to: Responsibilities: - Data Pipeline Development, Design & Automation: - Design and implement efficient database structures to ensure optimal performance and support analytics. - Design, implement, and optimize secure data pipelines to ingest, process, and store large volumes of structured and unstructured data from diverse sources, including vulnerability scans, security tools, and assessments. - Work closely with stakeholders to provide clean, structured datasets that enable advanced analytics and insights into cybersecurity risks, trends, and remediation activities. Technical Competencies: - 7+ years of Hands-on experience with Scala & Hands-on experience with Spark. - 10+ years of experience in designing and developing Data Pipelines for Data Ingestion or Transformation using Spark with Scala. - Good experience in Big Data technologies (HDFS, Hive, Apache Spark, Spark-SQL, Spark Streaming, Spark jobs optimization & Kafka). - Good knowledge of Exposure to various file formats (JSON, AVRO, Parquet). - Knowledge of agile (scrum) development methodology is a plus. - Strong development/automation skills. - Right attitude to participate and contribute through all phases of Development Lifecycle. - Secondary Skillset: No SQL, Starburst, Python. - Optional: Java Spring, Kubernetes, Docker. Competencies (Soft skills): - Strong communication skills. - Candidate should be responsible for reporting to both business and technology senior management. - Need to work with stakeholders and keep them updated on developments, estimation, delivery, and issues. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity, review Accessibility at Citi. View Citi's EEO Policy Statement and the Know Your Rights poster.,

You are a Staff Software Engineer (ETL) with 8-10 years of experience looking to join R1's ETL Development team. In this role, you will play a crucial part in designing, developing, and leading the implementation of ETL processes and data architecture solutions. Reporting to the Engineering Manager, you will be responsible for planning, designing, and implementing a centralized data warehouse solution for data acquisition, ingestion, large data processing, and automation/optimization across all company products. Your key responsibilities will include leading the design and architecture of ETL processes and data integration solutions, developing and maintaining ETL workflows using tools like SSIS, Azure Databricks, SparkSQL, or similar, collaborating with stakeholders to ensure seamless integration, transformation, and loading of data, optimizing ETL processes for performance, scalability, and reliability, conducting code reviews, providing technical guidance, mentoring junior developers, troubleshooting and resolving issues related to ETL processes and data integration, ensuring compliance with data governance, security policies, and best practices, documenting ETL processes, and staying updated with the latest trends and technologies in data integration and ETL. To qualify for this role, you should have a Bachelor's degree in computer science, Information Technology, or a related field, along with 10-12 years of experience in ETL development and data integration. You should possess expertise in ETL tools such as SSIS, T-SQL, Azure Databricks, or similar, knowledge of SQL/NoSQL data storage mechanisms and Big Data technologies, experience in Data Modeling, familiarity with Azure data factory, Azure Data bricks, Azure Data Lake, and experience in Scala, SparkSQL, Airflow is preferred. Strong problem-solving and analytical skills, excellent communication and leadership abilities, proficiency in working effectively in a team-oriented environment, experience with agile methodology, and healthcare industry experience are also preferred qualifications. At R1, you will have the opportunity to work in an evolving healthcare setting where shared expertise is utilized to deliver innovative solutions. The fast-growing team provides opportunities to learn and grow through rewarding interactions, collaboration, and the freedom to explore professional interests. Associates are encouraged to contribute, innovate, and create meaningful work that impacts the communities served globally. R1 also offers a culture of excellence that drives customer success, improves patient care, and believes in giving back to the community with a competitive benefits package. To learn more, visit r1rcm.com.,

As a Test Engineer, you will be responsible for supporting the AI & Data science teams in testing their AI/ML flows. You will analyze system specifications, develop detailed test plans and test cases, execute test cases, and identify defects. Your role includes documenting and reporting defects to the development team, collaborating with them to resolve issues, and ensuring that the software meets quality standards and best practices. Participation in review meetings to provide feedback is also part of your responsibilities. It is essential to have excellent knowledge of SDLC and STLC, along with expertise in Agile methodology. Your technical skills should include a strong understanding of Testing framework & automation concepts, as well as proficiency in Pandas, Python, Pytest, SQL, SparkSQL, Pyspark, and testing LLMs such as GPT, LLAMA, Gemma. Additionally, good database skills in any relational DB, hands-on experience with the Databricks Platform, and the ability to comprehend models and write Python scripts to test data inflow and outflow are required. You should also be proficient in Programming and Query Language, with knowledge of Cloud platforms, preferably Azure fundamentals and Azure analytics services. Writing test scripts from designs and expertise in Jira, Excel, and Confluence are important technical skills. In terms of soft skills, excellent verbal and written communication skills in English are necessary. You should be able to work both independently and as part of a team, demonstrating strong project leadership and communication skills, including customer-facing interactions. It would be beneficial to have skills in API testing, Test automation, Azure AI services, and any vector dB/Graph dB. Familiarity with ML NLP algorithms, entity mining & clustering, and sentiment analysis is also considered advantageous for this role.,

As a valued member of Infosys Consulting, you will play a crucial role in supporting large Oil & Gas/Utilities prospects by showcasing Infosys" unique value proposition through practical use cases across the value chain. Your responsibilities will include gathering, identifying, and documenting business requirements, as well as creating functional specifications for new systems and processes. Utilizing your expertise in assessing current processes, conducting gap analyses, and designing future processes, you will recommend changes and drive continuous improvement using methodologies such as Six Sigma and Lean. In your role, you will be involved in Technology Project Management, which includes overseeing technology vendors and client stakeholders. You will also manage large projects and programs in a multi-vendor, globally distributed team environment, leveraging Agile principles and DevOps capabilities. Collaboration with the IT Project Management Office will be essential as you support the implementation of client-specific digital solutions, from business case development to IT strategy and tool/software selection. Your expertise in designing and implementing scalable data pipelines, ETL/ELT workflows, and optimized data models across cloud data warehouses and lakes will enable reliable access to high-quality data for business insights and strategic decision-making. You will also be responsible for building and maintaining dashboards, reports, and visualizations using tools like Power BI and Tableau, while conducting deep-dive analyses to evaluate business performance and identify opportunities. Collaboration with business stakeholders to translate strategic objectives into data-driven solutions, defining KPIs, and enabling self-service analytics will be a key aspect of your role. Additionally, you will work closely with client IT teams and business stakeholders to uncover opportunities and derive actionable insights. Participation in internal firm-building activities and supporting sales efforts for new and existing clients through proposal creation and sales presentation facilitation will also be part of your responsibilities. To qualify for this position, you should have at least 3-5 years of experience in data engineering, ideally within the Oil & Gas or Utilities sector. Strong communication skills, both written and verbal, are essential, along with a proven track record in business analysis, product design, or project management. A Bachelor's degree or Full-time MBA/PGDM from Tier 1/Tier 2 B-Schools in India or a foreign equivalent is required. Preferred qualifications include knowledge of digital technologies and agile development practices, as well as the ability to work effectively in a cross-cultural team environment. Strong teamwork, communication skills, and the ability to interact with mid-level managers of client organizations are highly valued. This position is preferred to be located in Electronic City, Bengaluru, but other locations such as Hyderabad, Chennai, Pune, Gurgaon, and Chandigarh are also considered based on business needs. Please note that the job may require extended periods of computer work and communication via telephone, email, or face-to-face interactions.,