267 Aws Glue Jobs

Principal AWS Data Engineer Location : Bangalore Experience : 9 - 12 years Job Summary: In this key leadership role, you will lead the development of foundational components for a Lakehouse architecture on AWS and drive the migration of existing data processing workflows to the new Lakehouse solution. You will work across the Data Engineering organisation to design and implement scalable data infrastructure and processes using technologies such as Python, PySpark, EMR Serverless, Iceberg, Glue and Glue Data Catalog. The main goal of this position is to ensure successful migration and establish robust data quality governance across the new platform, enabling reliable and efficient data processing. Success in this role requires deep technical expertise, exceptional problem-solving skills, and the ability to lead and mentor within an agile team. Must Have Tech Skills: Prior Principal Engineer experience, leading team best practices in design, development, and implementation, mentoring team members, and fostering a culture of continuous learning and innovation Extensive experience in software architecture and solution design, including microservices, distributed systems, and cloud-native architectures. Expert in Python and Spark, with a deep focus on ETL data processing and data engineering practices. Deep technical knowledge of AWS data services and engineering practices, with demonstrable experience of implementing data pipelines using tools like EMR, AWS Glue, AWS Lambda, AWS Step Functions, API Gateway, Athena Experience of delivering Lakehouse solutions/architectures Nice To Have Tech Skills: Knowledge of additional programming languages and development tools to provide flexibility and adaptability across varied data engineering projects A master’s degree or relevant certifications (e.g., AWS Certified Solutions Architect, Certified Data Analytics) is advantageous Key Accountabilities: Lead complex projects autonomously, fostering an inclusive and open culture within development teams. Mentor team members and lead technical discussions. Provides strategic guidance on best practices in design, development, and implementation. Leads the development of high-quality, efficient code and develops necessary tools and applications to address complex business needs Collaborates closely with architects, Product Owners, and Dev team members to decompose solutions into Epics, leading the design and planning of these components. Drive the migration of existing data processing workflows to a Lakehouse architecture, leveraging Iceberg capabilities. Serves as an internal subject matter expert in software development, advising stakeholders on best practices in design, development, and implementation Key Skills: Deep technical knowledge of data engineering solutions and practices. Expert in AWS services and cloud solutions, particularly as they pertain to data engineering practices Extensive experience in software architecture and solution design Specialized expertise in Python and Spark Ability to provide technical direction, set high standards for code quality and optimize performance in data-intensive environments. Skilled in leveraging automation tools and Continuous Integration/Continuous Deployment (CI/CD) pipelines to streamline development, testing, and deployment. Exceptional communicator who can translate complex technical concepts for diverse stakeholders, including engineers, product managers, and senior executives. Provides thought leadership within the engineering team, setting high standards for quality, efficiency, and collaboration. Experienced in mentoring engineers, guiding them in advanced coding practices, architecture, and strategic problem-solving to enhance team capabilities. Educational Background: Bachelor’s degree in computer science, Software Engineering, or a related field is essential. Bonus Skills: Financial Services expertise preferred, working with Equity and Fixed Income asset classes and a working knowledge of Indices.

Job Summary: Experience : 5 - 8 Years Location : Bangalore Contribute to building state-of-the-art data platforms in AWS, leveraging Python and Spark. Be part of a dynamic team, building data solutions in a supportive and hybrid work environment. This role is ideal for an experienced data engineer looking to step into a leadership position while remaining hands-on with cutting-edge technologies. You will design, implement, and optimize ETL workflows using Python and Spark, contributing to our robust data Lakehouse architecture on AWS. Success in this role requires technical expertise, strong problem-solving skills, and the ability to collaborate effectively within an agile team. Must Have Tech Skills: Demonstrable experience as a senior data engineer. Expert in Python and Spark, with a deep focus on ETL data processing and data engineering practices. Experience of implementing data pipelines using tools like EMR, AWS Glue, AWS Lambda, AWS Step Functions, API Gateway, Athena Experience with data services in Lakehouse architecture. Good background and proven experience of data modelling for data platforms Nice To Have Tech Skills: A master’s degree or relevant certifications (e.g., AWS Certified Solutions Architect, Certified Data Analytics) is advantageous Key Accountabilities: Provides guidance on best practices in design, development, and implementation, ensuring solutions meet business requirements and technical standards. Works closely with architects, Product Owners, and Dev team members to decompose solutions into Epics, leading design and planning of these components. Drive the migration of existing data processing workflows to the Lakehouse architecture, leveraging Iceberg capabilities. Communicates complex technical information clearly, tailoring messages to the appropriate audience to ensure alignment. Key Skills: Deep technical knowledge of data engineering solutions and practices. Implementation of data pipelines using AWS data services and Lakehouse capabilities. Highly proficient in Python, Spark and familiar with a variety of development technologies. Skilled in decomposing solutions into components (Epics, stories) to streamline development. Proficient in creating clear, comprehensive documentation. Proficient in quality assurance practices, including code reviews, automated testing, and best practices for data validation. Previous Financial Services experience delivering data solutions against financial and market reference data. Solid grasp of Data Governance and Data Management concepts, including metadata management, master data management, and data quality. Educational Background: Bachelor’s degree in computer science, Software Engineering, or related field essential. Bonus Skills: A working knowledge of Indices, Index construction and Asset Management principles.

Job Summary: Experience : 4 - 8 years Location : Bangalore The Data Engineer will contribute to building state-of-the-art data Lakehouse platforms in AWS, leveraging Python and Spark. You will be part of a dynamic team, building innovative and scalable data solutions in a supportive and hybrid work environment. You will design, implement, and optimize workflows using Python and Spark, contributing to our robust data Lakehouse architecture on AWS. Success in this role requires previous experience of building data products using AWS services, familiarity with Python and Spark, problem-solving skills, and the ability to collaborate effectively within an agile team. Must Have Tech Skills: Demonstrable previous experience as a data engineer. Technical knowledge of data engineering solutions and practices. Implementation of data pipelines using tools like EMR, AWS Glue, AWS Lambda, AWS Step Functions, API Gateway, Athena Proficient in Python and Spark, with a focus on ETL data processing and data engineering practices. Nice To Have Tech Skills: Familiar with data services in a Lakehouse architecture. Familiar with technical design practices, allowing for the creation of scalable, reliable data products that meet both technical and business requirements A master’s degree or relevant certifications (e.g., AWS Certified Solutions Architect, Certified Data Analytics) is advantageous Key Accountabilities: Writes high quality code, ensuring solutions meet business requirements and technical standards. Works with architects, Product Owners, and Development leads to decompose solutions into Epics, assisting the design and planning of these components. Creates clear, comprehensive technical documentation that supports knowledge sharing and compliance. Experience in decomposing solutions into components (Epics, stories) to streamline development. Actively contributes to technical discussions, supporting a culture of continuous learning and innovation. Key Skills: Proficient in Python and familiar with a variety of development technologies. Previous experience of implementing data pipelines, including use of ETL tools to streamline data ingestion, transformation, and loading. Solid understanding of AWS services and cloud solutions, particularly as they pertain to data engineering practices. Familiar with AWS solutions including IAM, Step Functions, Glue, Lambda, RDS, SQS, API Gateway, Athena. Proficient in quality assurance practices, including code reviews, automated testing, and best practices for data validation. Experienced in Agile development, including sprint planning, reviews, and retrospectives Educational Background: Bachelor’s degree in computer science, Software Engineering, or related essential. Bonus Skills: Financial Services expertise preferred, working with Equity and Fixed Income asset classes and a working knowledge of Indices. Familiar with implementing and optimizing CI/CD pipelines. Understands the processes that enable rapid, reliable releases, minimizing manual effort and supporting agile development cycles.

Hello Talented Techie! We provide support in Project Services and Transformation, Digital Solutions and Delivery Management. We offer joint operations and digitalization services for Global Business Services and work closely alongside the entire Shared Services organization. We make optimal use of the possibilities of new technologies such as Business Process Management (BPM) and Robotics as enablers for efficient and effective processes. We are looking for Sr. AWS Cloud Architect Architect and Design Develop scalable and efficient data solutions using AWS services such as AWS Glue, Amazon Redshift, S3, Kinesis(Apache Kafka), DynamoDB, Lambda, AWS Glue(Streaming ETL) and EMR Integration Integrate real-time data from various Siemens organizations into our data lake, ensuring seamless data flow and processing. Data Lake Management Design and manage a large-scale data lake using AWS services like S3, Glue, and Lake Formation. Data Transformation Apply various data transformations to prepare data for analysis and reporting, ensuring data quality and consistency. Snowflake Integration Implement and manage data pipelines to load data into Snowflake, utilizing Iceberg tables for optimal performance and flexibility. Performance Optimization Optimize data processing pipelines for performance, scalability, and cost-efficiency. Security and Compliance Ensure that all solutions adhere to security best practices and compliance requirements. Collaboration Work closely with cross-functional teams, including data engineers, data scientists, and application developers, to deliver end-to-end solutions. Monitoring and Troubleshooting Implement monitoring solutions to ensure the reliability and performance of data pipelines. Troubleshoot and resolve any issues that arise. Youd describe yourself as: Experience 8+ years of experience in data engineering or cloud solutioning, with a focus on AWS services. Technical Skills Proficiency in AWS services such as AWS API, AWS Glue, Amazon Redshift, S3, Apache Kafka and Lake Formation. Experience with real-time data processing and streaming architectures. Big Data Querying Tools: Strong knowledge of big data querying tools (e.g., Hive, PySpark). Programming Strong programming skills in languages such as Python, Java, or Scala for building and maintaining scalable systems. Problem-Solving Excellent problem-solving skills and the ability to troubleshoot complex issues. Communication Strong communication skills, with the ability to work effectively with both technical and non-technical stakeholders. Certifications AWS certifications are a plus. Create a better #TomorrowWithUs! This role, based in Bangalore, is an individual contributor position. You may be required to visit other locations within India and internationally. In return, you'll have the opportunity to work with teams shaping the future. At Siemens, we are a collection of over 312,000 minds building the future, one day at a time, worldwide. Find out more about Siemens careers at

Project Role : Application Developer Project Role Description : Design, build and configure applications to meet business process and application requirements. Must have skills : AWS Glue Good to have skills : Microsoft SQL Server, Python (Programming Language), Data EngineeringMinimum 5 year(s) of experience is required Educational Qualification : 15 years full time education:Developing a customer insights platform that will provide an ID graph and Digital customer view to help drive improvements in marketing decisions. Responsibilities:Design, build, and maintain data pipelines using AWS services (Glue, Neptune, S3).Participate in code reviews, testing, and optimization of data pipelines.Collaborate with stakeholders to understand data requirements and translate into technical solutions.:Proven experience as a Senior Data Engineer / Data Architect, or similar role.Knowledge of data governance and security practices.Extensive experience with data lake technologies (NiFi, Spark, Hive Metastore, Object Storage, Delta Lake Framework)Extensive experience with AWS cloud services, including AWS Glue, Neptune, S3 and LambdaExperience with AWS Neptune or other graph database technologies.Experience in data modelling and design.Experience with event driven architectureExperience with PythonExperience with SQLStrong problem-solving skills and attention to detail.Excellent communication and teamwork skills. Nice to have:Experience with observability solutions (Splunk, New Relic)Experience with Infrastructure as Code (Terraform, CloudFormation)Experience with CICD (Jenkins)Experience with KubernetesFamiliarity with data visualization tools.Support Engineer Similar skills as the above, but with more of a support focus, able to troubleshoot, patch and upgrade, minor enhancements and fixes to the infrastructure and pipelines. Experience with observability, cloudwatch, new relic and monitoring. Qualification 15 years full time education

Experience: 8+ years of experience in data engineering, specifically in cloud environments like AWS. Proficiency in PySpark for distributed data processing and transformation. Solid experience with AWS Glue for ETL jobs and managing data workflows. Hands-on experience with AWS Data Pipeline (DPL) for workflow orchestration. Strong experience with AWS services such as S3, Lambda, Redshift, RDS, and EC2. Technical Skills: Proficiency in Python and PySpark for data processing and transformation tasks. Deep understanding of ETL concepts and best practices. Familiarity with AWS Glue (ETL jobs, Data Catalog, and Crawlers). Experience building and maintaining data pipelines with AWS Data Pipeline or similar orchestration tools. Familiarity with AWS S3 for data storage and management, including file formats (CSV, Parquet, Avro). Strong knowledge of SQL for querying and manipulating relational and semi-structured data. Experience with Data Warehousing and Big Data technologies, specifically within AWS. Additional Skills: Experience with AWS Lambda for serverless data processing and orchestration. Understanding of AWS Redshift for data warehousing and analytics. Familiarity with Data Lakes, Amazon EMR, and Kinesis for streaming data processing. Knowledge of data governance practices, including data lineage and auditing. Familiarity with CI/CD pipelines and Git for version control. Experience with Docker and containerization for building and deploying applications. Design and Build Data PipelinesDesign, implement, and optimize data pipelines on AWS using PySpark, AWS Glue, and AWS Data Pipeline to automate data integration, transformation, and storage processes. ETL DevelopmentDevelop and maintain Extract, Transform, and Load (ETL) processes using AWS Glue and PySpark to efficiently process large datasets. Data Workflow AutomationBuild and manage automated data workflows using AWS Data Pipeline, ensuring seamless scheduling, monitoring, and management of data jobs. Data IntegrationWork with different AWS data storage services (e.g., S3, Redshift, RDS) to ensure smooth integration and movement of data across platforms. Optimization and ScalingOptimize and scale data pipelines for high performance and cost efficiency, utilizing AWS services like Lambda, S3, and EC2.

Sr Developer with special emphasis and experience of 8 to 10 years on Python and Pyspark along with hands on experience on AWS Data components like AWS Glue, Athena etc.,. Also have good knowledge on Data ware house tools to understand the existing system. Candidate should also have experience on Datalake, Teradata and Snowflake. Should be good at terraform. 8-10 years of experience in designing and developing Python and Pyspark applications Creating or maintaining data lake solutions using Snowflake,taradata and other dataware house tools. Should have good knowledge and hands on experience on AWS Glue , Athena etc., Sound Knowledge on all Data lake concepts and able to work on data migration projects. Providing ongoing support and maintenance for applications, including troubleshooting and resolving issues. Expertise in practices like Agile, Peer reviews and CICD Pipelines.

Sr Developer with special emphasis and experience of 8 to 10 years on Python and Pyspark along with hands on experience on AWS Data components like AWS Glue, Athena etc.,. Also have good knowledge on Data ware house tools to understand the existing system. Candidate should also have experience on Datalake, Teradata and Snowflake. Should be good at terraform. 8-10 years of experience in designing and developing Python and Pyspark applications Creating or maintaining data lake solutions using Snowflake,taradata and other dataware house tools. Should have good knowledge and hands on experience on AWS Glue , Athena etc., Sound Knowledge on all Data lake concepts and able to work on data migration projects. Providing ongoing support and maintenance for applications, including troubleshooting and resolving issues. Expertise in practices like Agile, Peer reviews and CICD Pipelines.

Educational Bachelor of Engineering,Bachelor Of Technology,Bachelor Of Science,Bachelor Of Comp. Applications,Master Of Engineering,Master Of Technology,Master Of Comp. Applications,Master Of Science Service Line Engineering Services Responsibilities A day in the life of an Infoscion As part of the Infosys consulting team, your primary role would be to get to the heart of customer issues, diagnose problem areas, design innovative solutions and facilitate deployment resulting in client delight. You will develop a proposal by owning parts of the proposal document and by giving inputs in solution design based on areas of expertise. You will plan the activities of configuration, configure the product as per the design, conduct conference room pilots and will assist in resolving any queries related to requirements and solution design You will conduct solution/product demonstrations, POC/Proof of Technology workshops and prepare effort estimates which suit the customer budgetary requirements and are in line with organization’s financial guidelines Actively lead small projects and contribute to unit-level and organizational initiatives with an objective of providing high quality value adding solutions to customers. If you think you fit right in to help our clients navigate their next in their digital transformation journey, this is the place for you! Additional Responsibilities: Ability to develop value-creating strategies and models that enable clients to innovate, drive growth and increase their business profitability Good knowledge on software configuration management systems Awareness of latest technologies and Industry trends Logical thinking and problem solving skills along with an ability to collaborate Understanding of the financial processes for various types of projects and the various pricing models available Ability to assess the current processes, identify improvement areas and suggest the technology solutions One or two industry domain knowledge Client Interfacing skills Project and Team management Technical and Professional : Primary skills- Groovy, Java, Postgres, AWS Preferred Skills: Technology-Cloud Platform-AWS Database Technology-Java-Java - ALL Technology-Ruby on Rails-MySql Postgres Oracle cucumber

Educational Bachelor of Engineering,Bachelor Of Technology Service Line Strategic Technology Group Responsibilities Power Programmer is an important initiative within Global Delivery to develop a team of Full Stack Developers who will be working on complex engineering projects, platforms and marketplaces for our clients using emerging technologies., They will be ahead of the technology curve and will be constantly enabled and trained to be Polyglots., They are Go-Getters with a drive to solve end customer challenges and will spend most of their time in designing and coding, End to End contribution to technology oriented development projects., Providing solutions with minimum system requirements and in Agile Mode., Collaborate with Power Programmers., Open Source community and Tech User group., Custom Development of new Platforms & Solutions ,Opportunities., Work on Large Scale Digital Platforms and marketplaces., Work on Complex Engineering Projects using cloud native architecture ., Work with innovative Fortune 500 companies in cutting edge technologies., Co create and develop New Products and Platforms for our clients., Contribute to Open Source and continuously upskill in latest technology areas., Incubating tech user group Technical and Professional : Must HaveJava, Microservices, Spring boot (with knowledge of Cloud Implementation - AWS, Azure or GCP, Kubernetes/Docker), Designing Skills (Designing Patterns), Data Structures, Angular (Any front end tech stack) Preferred Skills: Technology-Cloud Platform-AWS Database-AWS Technology-Java-Core Java Technology-Microservices-Microservices API Management Technology-UI & Markup Language-Angular JS/Angular 1.x-Angular 2 Technology-Reactive Programming-react JS Technology-Algorithms and Data Structures-Algorithms and Data Structures - ALL Technology-Java-Springboot Technology-Full stack-Java Full stack Foundational -SDLC-Architecture Designing

Key Responsibilities Set up and maintain monitoring dashboards for ETL jobs using Datadog, including metrics, logs, and alerts. Monitor daily ETL workflows and proactively detect and resolve data pipeline failures or performance issues. Create Datadog Monitors for job status (success/failure), job duration, resource utilization, and error trends. Work closely with Data Engineering teams to onboard new pipelines and ensure observability best practices. Integrate Datadog with tools. Conduct root cause analysis of ETL failures and performance bottlenecks. Tune thresholds, baselines, and anomaly detection settings in Datadog to reduce false positives. Document incident handling procedures and contribute to improving overall ETL monitoring maturity. Participate in on call rotations or scheduled support windows to manage ETL health. Required Skills & Qualifications 3+ years of experience in ETL/data pipeline monitoring, preferably in a cloud or hybrid environment. Proficiency in using Datadog for metrics, logging, alerting, and dashboards. Strong understanding of ETL concepts and tools (e.g., Airflow, Informatica, Talend, AWS Glue, or dbt). Familiarity with SQL and querying large datasets. Experience working with Python, Shell scripting, or Bash for automation and log parsing. Understanding of cloud platforms (AWS/GCP/Azure) and services like S3, Redshift, BigQuery, etc. Knowledge of CI/CD and DevOps principles related to data infrastructure monitoring. Preferred Qualifications Experience with distributed tracing and APM in Datadog. Prior experience monitoring Spark, Kafka, or streaming pipelines. Familiarity with ticketing tools (e.g., Jira, ServiceNow) and incident management workflows.

Sr Developer with special emphasis and experience of 8 to 10 years on Python and Pyspark along with hands on experience on AWS Data components like AWS Glue, Athena etc.,. Also have good knowledge on Data ware house tools to understand the existing system. Candidate should also have experience on Datalake, Teradata and Snowflake. Should be good at terraform. 8-10 years of experience in designing and developing Python and Pyspark applications Creating or maintaining data lake solutions using Snowflake,taradata and other dataware house tools. Should have good knowledge and hands on experience on AWS Glue , Athena etc., Sound Knowledge on all Data lake concepts and able to work on data migration projects. Providing ongoing support and maintenance for applications, including troubleshooting and resolving issues. Expertise in practices like Agile, Peer reviews and CICD Pipelines.

Sr Devloper with special emphasis and experience of 8 to 10 years on Python and Pyspark along with hands on experience on AWS Data components like AWS Glue, Athena etc.,. Also have good knowledge on Data ware house tools to understand the existing system. Candidate should also have experience on Datalake, Teradata and Snowflake. Should be good at terraform. 8-10 years of experience in designing and developing Python and Pyspark applications Creating or maintaining data lake solutions using Snowflake,taradata and other dataware house tools. Should have good knowledge and hands on experience on AWS Glue , Athena etc., Sound Knowledge on all Data lake concepts and able to work on data migration projects. Providing ongoing support and maintenance for applications, including troubleshooting and resolving issues. Expertise in practices like Agile, Peer reviews and CICD Pipelines.

Experience: 8 years of experience in data engineering, specifically in cloud environments like AWS. Proficiency in PySpark for distributed data processing and transformation. Solid experience with AWS Glue for ETL jobs and managing data workflows. Hands-on experience with AWS Data Pipeline (DPL) for workflow orchestration. Strong experience with AWS services such as S3, Lambda, Redshift, RDS, and EC2. Technical Skills: Proficiency in Python and PySpark for data processing and transformation tasks. Deep understanding of ETL concepts and best practices. Familiarity with AWS Glue (ETL jobs, Data Catalog, and Crawlers). Experience building and maintaining data pipelines with AWS Data Pipeline or similar orchestration tools. Familiarity with AWS S3 for data storage and management, including file formats (CSV, Parquet, Avro). Strong knowledge of SQL for querying and manipulating relational and semi-structured data. Experience with Data Warehousing and Big Data technologies, specifically within AWS. Additional Skills: Experience with AWS Lambda for serverless data processing and orchestration. Understanding of AWS Redshift for data warehousing and analytics. Familiarity with Data Lakes, Amazon EMR, and Kinesis for streaming data processing. Knowledge of data governance practices, including data lineage and auditing. Familiarity with CI/CD pipelines and Git for version control. Experience with Docker and containerization for building and deploying applications. Design and Build Data PipelinesDesign, implement, and optimize data pipelines on AWS using PySpark, AWS Glue, and AWS Data Pipeline to automate data integration, transformation, and storage processes. ETL DevelopmentDevelop and maintain Extract, Transform, and Load (ETL) processes using AWS Glue and PySpark to efficiently process large datasets. Data Workflow AutomationBuild and manage automated data workflows using AWS Data Pipeline, ensuring seamless scheduling, monitoring, and management of data jobs. Data IntegrationWork with different AWS data storage services (e.g., S3, Redshift, RDS) to ensure smooth integration and movement of data across platforms. Optimization and ScalingOptimize and scale data pipelines for high performance and cost efficiency, utilizing AWS services like Lambda, S3, and EC2.

1. Experience of working in AWS cloud service (i.e. S3, AWS Glue, Glue catalogue, Step Functions, lambda, Event Bridge etc) 2. Must have hands on DQ Libraries for data quality checks 3. Proficiency in data modelling and database management. 4. Strong programming skills in python, unix and on ETL technologies like Informatica 5. Experience of DevOps and Agile methodology and associated toolsets (including working with code repositories) and methodologies 6. Knowledge of big data technologies like Hadoop and Spark. 7. Must have hands on Reporting tools Tableau, quick sight and MS Power BI 8. Must have hands on databases like Postgres, MongoDB 9. Experience of using industry recognised frameworks and experience on Streamsets & Kafka is preferred 10. Experience in data sourcing including real time data integration 11. Proficiency in Snowflake Cloud and associated data migration from on premise to Cloud with knowledge on databases like Snowflake, Azure data lake, Postgres

Project Role : Data Engineer Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems. Must have skills : Apache Spark Good to have skills : AWS GlueMinimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Data Engineer, you will design, develop, and maintain data solutions that facilitate data generation, collection, and processing. Your typical day will involve creating data pipelines, ensuring data quality, and implementing ETL processes to migrate and deploy data across various systems. You will collaborate with cross-functional teams to understand data requirements and optimize data workflows, ensuring that the data infrastructure supports the organization's analytical needs effectively. Roles & Responsibilities:- Expected to be an SME.- Collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Provide solutions to problems for their immediate team and across multiple teams.- Mentor junior team members to enhance their skills and knowledge in data engineering.- Continuously evaluate and improve data processing workflows to enhance efficiency and performance. Professional & Technical Skills: - Must To Have Skills: Proficiency in Apache Spark.- Good To Have Skills: Experience with AWS Glue.- Strong understanding of data pipeline architecture and design.- Experience with ETL processes and data integration techniques.- Familiarity with data quality frameworks and best practices. Additional Information:- The candidate should have minimum 5 years of experience in Apache Spark.- This position is based at our Hyderabad office.- A 15 years full time education is required. Qualification 15 years full time education

Project Role : Data Engineer Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems. Must have skills : Apache Spark Good to have skills : AWS GlueMinimum 3 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Data Engineer, you will design, develop, and maintain data solutions that facilitate data generation, collection, and processing. Your typical day will involve creating data pipelines, ensuring data quality, and implementing ETL processes to effectively migrate and deploy data across various systems. You will collaborate with cross-functional teams to understand data requirements and contribute to the overall data strategy of the organization, ensuring that data solutions are efficient, scalable, and aligned with business objectives. You will also monitor and optimize existing data processes to enhance performance and reliability, making data accessible and actionable for stakeholders. Roles & Responsibilities:- Expected to perform independently and become an SME.- Required active participation/contribution in team discussions.- Contribute in providing solutions to work related problems.- Collaborate with data architects and analysts to design data models that meet business needs.- Develop and maintain documentation for data processes and workflows to ensure clarity and compliance. Professional & Technical Skills: - Must To Have Skills: Proficiency in Apache Spark.- Good To Have Skills: Experience with AWS Glue.- Strong understanding of data processing frameworks and methodologies.- Experience in building and optimizing data pipelines for performance and scalability.- Familiarity with data warehousing concepts and best practices. Additional Information:- The candidate should have minimum 3 years of experience in Apache Spark.- This position is based at our Bengaluru office.- A 15 years full time education is required. Qualification 15 years full time education

The candidate must possess knowledge relevant to the functional area, and act as a subject matter expert in providing advice in the area of expertise, and also focus on continuous improvement for maximum efficiency. It is vital to focus on the high standard of delivery excellence, provide top-notch service quality and develop successful long-term business partnerships with internal/external customers by identifying and fulfilling customer needs. He/she should be able to break down complex problems into logical and manageable parts in a systematic way, and generate and compare multiple options, and set priorities to resolve problems. The ideal candidate must be proactive, and go beyond expectations to achieve job results and create new opportunities. He/she must positively influence the team, motivate high performance, promote a friendly climate, give constructive feedback, provide development opportunities, and manage career aspirations of direct reports. Communication skills are key here, to explain organizational objectives, assignments, and the big picture to the team, and to articulate team vision and clear objectives. Process ManagerRoles and responsibilities: Designing and implementing scalable, reliable, and maintainable data architectures on AWS. Developing data pipelines to extract, transform, and load (ETL) data from various sources into AWS environments. Creating and optimizing data models and schemas for performance and scalability using AWS services like Redshift, Glue, Athena, etc. Integrating AWS data solutions with existing systems and third-party services. Monitoring and optimizing the performance of AWS data solutions, ensuring efficient query execution and data retrieval. Implementing data security and encryption best practices in AWS environments. Documenting data engineering processes, maintaining data pipeline infrastructure, and providing support as needed. Working closely with cross-functional teams including data scientists, analysts, and stakeholders to understand data requirements and deliver solutions. Technical and Functional Skills: Typically, a bachelors degree in Computer Science, Engineering, or a related field is required, along with 5+ years of experience in data engineering and AWS cloud environments. Strong experience with AWS data services such as S3, EC2, Redshift, Glue, Athena, EMR, etc Proficiency in programming languages commonly used in data engineering such as Python, SQL, Scala, or Java. Experience in designing, implementing, and optimizing data warehouse solutions on Snowflake/ Amazon Redshift. Familiarity with ETL tools and frameworks (e.g., Apache Airflow, AWS Glue) for building and managing data pipelines. Knowledge of database management systems (e.g., PostgreSQL, MySQL, Amazon Redshift) and data lake concepts. Understanding of big data technologies such as Hadoop, Spark, Kafka, etc., and their integration with AWS. Proficiency in version control tools like Git for managing code and infrastructure as code (e.g., CloudFormation, Terraform). Ability to analyze complex technical problems and propose effective solutions. Strong verbal and written communication skills for documenting processes and collaborating with team members and stakeholders.

The candidate must possess knowledge relevant to the functional area, and act as a subject matter expert in providing advice in the area of expertise, and also focus on continuous improvement for maximum efficiency. It is vital to focus on the high standard of delivery excellence, provide top-notch service quality and develop successful long-term business partnerships with internal/external customers by identifying and fulfilling customer needs. He/she should be able to break down complex problems into logical and manageable parts in a systematic way, and generate and compare multiple options, and set priorities to resolve problems. The ideal candidate must be proactive, and go beyond expectations to achieve job results and create new opportunities. He/she must positively influence the team, motivate high performance, promote a friendly climate, give constructive feedback, provide development opportunities, and manage career aspirations of direct reports. Communication skills are key here, to explain organizational objectives, assignments, and the big picture to the team, and to articulate team vision and clear objectives. Process ManagerRoles and responsibilities: Designing and implementing scalable, reliable, and maintainable data architectures on AWS. Developing data pipelines to extract, transform, and load (ETL) data from various sources into AWS environments. Creating and optimizing data models and schemas for performance and scalability using AWS services like Redshift, Glue, Athena, etc. Integrating AWS data solutions with existing systems and third-party services. Monitoring and optimizing the performance of AWS data solutions, ensuring efficient query execution and data retrieval. Implementing data security and encryption best practices in AWS environments. Documenting data engineering processes, maintaining data pipeline infrastructure, and providing support as needed. Working closely with cross-functional teams including data scientists, analysts, and stakeholders to understand data requirements and deliver solutions. Technical and Functional Skills: Typically, a bachelors degree in Computer Science, Engineering, or a related field is required, along with 5+ years of experience in data engineering and AWS cloud environments. Strong experience with AWS data services such as S3, EC2, Redshift, Glue, Athena, EMR, etc Proficiency in programming languages commonly used in data engineering such as Python, SQL, Scala, or Java. Experience in designing, implementing, and optimizing data warehouse solutions on Snowflake/ Amazon Redshift. Familiarity with ETL tools and frameworks (e.g., Apache Airflow, AWS Glue) for building and managing data pipelines. Knowledge of database management systems (e.g., PostgreSQL, MySQL, Amazon Redshift) and data lake concepts. Understanding of big data technologies such as Hadoop, Spark, Kafka, etc., and their integration with AWS. Proficiency in version control tools like Git for managing code and infrastructure as code (e.g., CloudFormation, Terraform). Ability to analyze complex technical problems and propose effective solutions. Strong verbal and written communication skills for documenting processes and collaborating with team members and stakeholders.

Process Manager - AWS Data Engineer Mumbai/Pune| Full-time (FT) | Technology Services Shift Timings - EMEA(1pm-9pm)|Management Level - PM| Travel - NA The ideal candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The role enables to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Process Manager Roles and responsibilities: Understand clients requirement and provide effective and efficient solution in AWS using Snowflake. Assembling large, complex sets of data that meet non-functional and functional business requirements Using Snowflake / Redshift Architect and design to create data pipeline and consolidate data on data lake and Data warehouse. Demonstrated strength and experience in data modeling, ETL development and data warehousing concepts Understanding data pipelines and modern ways of automating data pipeline using cloud based Testing and clearly document implementations, so others can easily understand the requirements, implementation, and test conditions Perform data quality testing and assurance as a part of designing, building and implementing scalable data solutions in SQL Technical and Functional Skills: AWS ServicesStrong experience with AWS data services such as S3, EC2, Redshift, Glue, Athena, EMR, etc. Programming LanguagesProficiency in programming languages commonly used in data engineering such as Python, SQL, Scala, or Java. Data WarehousingExperience in designing, implementing, and optimizing data warehouse solutions on Snowflake/ Amazon Redshift. ETL ToolsFamiliarity with ETL tools and frameworks (e.g., Apache Airflow, AWS Glue) for building and managing data pipelines. Database ManagementKnowledge of database management systems (e.g., PostgreSQL, MySQL, Amazon Redshift) and data lake concepts. Big Data TechnologiesUnderstanding of big data technologies such as Hadoop, Spark, Kafka, etc., and their integration with AWS. Version ControlProficiency in version control tools like Git for managing code and infrastructure as code (e.g., CloudFormation, Terraform). Problem-solving Skills: Ability to analyze complex technical problems and propose effective solutions. Communication Skills: Strong verbal and written communication skills for documenting processes and collaborating with team members and stakeholders. Education and ExperienceTypically, a bachelors degree in Computer Science, Engineering, or a related field is required, along with 5+ years of experience in data engineering and AWS cloud environments. About eClerx eClerx is a global leader in productized services, bringing together people, technology and domain expertise to amplify business results. Our mission is to set the benchmark for client service and success in our industry. Our vision is to be the innovation partner of choice for technology, data analytics and process management services. Since our inception in 2000, we've partnered with top companies across various industries, including financial services, telecommunications, retail, and high-tech. Our innovative solutions and domain expertise help businesses optimize operations, improve efficiency, and drive growth. With over 18,000 employees worldwide, eClerx is dedicated to delivering excellence through smart automation and data-driven insights. At eClerx, we believe in nurturing talent and providing hands-on experience. About eClerx Technology eClerxs Technology Group collaboratively delivers Analytics, RPA, AI, and Machine Learning digital technologies that enable our consultants to help businesses thrive in a connected world. Our consultants and specialists partner with our global clients and colleagues to build and implement digital solutions through a broad spectrum of activities. To know more about us, visit https://eclerx.com eClerx is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability or protected veteran status, or any other legally protected basis, per applicable law

Urgent Requirement for Pyspark,sql & aws glue Experience:6+ Years Location:Pan india Mandatory Skills pyspark,sql & aws glue Good to have skills snowflake & snowpark.

Immediate Openings on AWS Cloud Developer _ Bengaluru _Contract Skill: AWS Cloud Developer Notice Period: Immediate . Employment Type: Contract Job Description Plan, design, and execute end-to-end data migration projects from various data sources to Amazon Aurora PostgreSQL and Amazon DynamoDB. Collaborate with cross-functional teams to understand data requirements, perform data analysis, and define migration strategies. Develop and implement data transformation and manipulation procedures using Talend, AWS Glue, and AWS DMS to ensure data accuracy and integrity during the migration process. Optimize data migration workflows for efficiency and reliability, and monitor performance to identify and address potential bottlenecks. Collaborate with database administrators, data engineers, and developers to troubleshoot and resolve data-related issues. Ensure adherence to best practices, security standards, and compliance requirements throughout the data migration process. Provide documentation, technical guidance, and training to team members and stakeholders on data migration procedures and best practices.

Mandatory skills: AWS Python

Position Overview Summary: The Data Engineer will expand and optimize the data and data pipeline architecture, as well as optimize data flow and collection for cross functional teams. The Data Engineer will perform data architecture analysis, design, development and testing to deliver data applications, services, interfaces, ETL processes, reporting and other workflow and management initiatives. The role also will follow modern SDLC principles, test driven development and source code reviews and change control standards in order to maintain compliance with policies. This role requires a highly motivated individual with strong technical ability, data capability, excellent communication and collaboration skills including the ability to develop and troubleshoot a diverse range of problems. Responsibilities Design and develop enterprise data data architecture solutions using Hadoop and other data technologies like Spark, Scala.

Company: Marsh McLennan Agency Description: Marsh McLennan is seeking candidates for the following position based in the Pune 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 (NYSEMMC) is the worlds leading professional services firm in the areas ofrisk, 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.Marshprovides 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 onLinkedIn andX . 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 (NYSEMMC) is a global leader in risk, strategy and people, advising clients in 130 countries across four businessesMarsh, 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.