38 Workflow Orchestration Jobs - Page 2

7+ years of experience in back-end development with Java/Spring Boot. 4+ years of hands-on experience with Camunda BPM for workflow and decision modeling. Expertise in BPMN 2.0, DMN, and workflow orchestration. Experience with Camunda Optimize and Tasklist. Strong experience with REST API integration and microservice architecture. Solid understanding of software development lifecycle (SDLC) and agile methodologies. Excellent problem-solving skills and ability to debug complex workflow scenarios. Strong communication and interpersonal skills Design and implement business workflows and decision models using Camunda BPMN and DMN. Integrate Camunda with enterprise systems using Java/Spring Boot and REST APIs Develop scalable, maintainable, and high-performance process applications.

10+ years of experience in back-end development with Java/Spring Boot. 4+ years of hands-on experience with Camunda BPM for workflow and decision modeling. Expertise in BPMN 2.0, DMN, and workflow orchestration. Experience with Camunda Optimize and Tasklist. Strong experience with REST API integration and microservice architecture. Solid understanding of software development lifecycle (SDLC) and agile methodologies. Excellent problem-solving skills and ability to debug complex workflow scenarios. Strong communication and interpersonal skills Design and implement business workflows and decision models using Camunda BPMN and DMN. Integrate Camunda with enterprise systems using Java/Spring Boot and REST APIs Develop scalable, maintainable, and high-performance process applications.

Capgemini Invent Capgemini Invent is the digital innovation, consulting and transformation brand of the Capgemini Group, a global business line that combines market leading expertise in strategy, technology, data science and creative design, to help CxOs envision and build what’s next for their businesses. Your Role Solution Design & Architecture Implementation & Deployment Technical Leadership & Guidance Client Engagement & Collaboration Performance Monitoring & Optimization Your Profile Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 3-8 years of experience in designing, implementing, and managing data solutions. 3-8 years of hands-on experience working with Google Cloud Platform (GCP) data services. Strong expertise in core GCP data services, including BigQuery (Data Warehousing) Cloud Storage (Data Lake) Dataflow (ETL/ELT) Cloud Composer (Workflow Orchestration - Apache Airflow) Pub/Sub and Dataflow (Streaming Data) Cloud Data Fusion (Graphical Data Integration) Dataproc (Managed Hadoop and Spark) Proficiency in SQL and experience with data modeling techniques. Experience with at least one programming language (e.g., Python, Java, Scala). Experience with Infrastructure-as-Code (IaC) tools such as Terraform or Cloud Deployment Manager. Understanding of data governance, security, and compliance principles in a cloud environment. Experience with CI/CD pipelines and DevOps practices. Excellent problem-solving, analytical, and communication skills. Ability to work independently and as part of a collaborative team. What you will love about working here We recognize the significance of flexible work arrangements to provide support. Be it remote work, or flexible work hours, you will get an environment to maintain healthy work life balance. At the heart of our mission is your career growth. Our array of career growth programs and diverse professions are crafted to support you in exploring a world of opportunities. Equip yourself with valuable certifications in the latest technologies such as Generative AI. About Capgemini Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2023 global revenues of "22.5 billion.

AWS Engineer1 TitleAWS Engineer Location: Offshore (Remote) Job Overview: We are seeking a skilled AWS Engineer to support the buildout and scaling of CodePulse , an internal engineering metrics platform. This is a contract position for 36 months , focused on implementing AWS infrastructure for high-throughput metric ingestion and analytics. The ideal candidate has a strong track record of building scalable, event-driven systems using core AWS services such as ECS Fargate , SQS , API Gateway , RDS , S3 , and Elasticache . Experience working on similar data processing or pipeline-based platforms is highly desirable. Key Responsibilities: Design, implement, and maintain secure, auto-scaling AWS infrastructure for a container-based microservice application. Deploy ECS (Fargate) workloads that process messages from SQS queues and write results to RDS and S3. Set up and tune CloudWatch alarms, logs, and metrics for system observability and alerting. Configure and optimize infrastructure componentsSQS, SNS, API Gateway, RDS (PostgreSQL), ElastiCache (Redis), and S3. Support integration with GitHub and Jira by securely handling API credentials, tokens, and webhook flows. Write and manage infrastructure-as-code using Terraform or AWS CDK, with support for versioning and team hand-off. Work with internal engineers to troubleshoot issues, optimize performance, and manage deployment workflows. Qualifications: 4-6 years of hands-on experience working as an AWS DevOps or Cloud Engineer. Proven experience deploying and scaling services using ECS Fargate , SQS , API Gateway , RDS (Postgres) , and S3 . Experience with Redis caching using Elasticache and familiarity with tuning cache strategies. Strong experience with CloudWatch , including logs, alarms, and dashboard setup. Proficient with Terraform or AWS CDK for infrastructure automation. Strong understanding of VPCs, IAM roles and policies, TLS, and secure communication patterns. Demonstrated experience building or supporting event-driven microservices in a production setting. Ability to work independently in a remote, distributed team and communicate clearly. Preferred Qualifications: Experience building internal tools or platforms with metric processing , workflow orchestration , or CI/CD integration . Familiarity with GitHub Actions , Docker , and container image deployment via ECR. Experience optimizing AWS infrastructure for cost efficiency and auto-scaling under burst loads . Prior experience integrating with third-party APIs like GitHub, Jira, or ServiceNow (optional but a plus). Location - Pune,Hyderabad,Kolkata,Jaipur,Chandigarh

Role & responsibilities Install & Upgrade AVEVA MES & System Platform solutions Design, configure, and deploy AVEVA MES solutions (Operations, Performance, and Quality modules) Develop and maintain MES workflows, data models, and reports for real-time production monitoring Integrate MES with SCADA, PLCs, and ERP systems using OPC, REST APIs, and SQL databases Implement traceability, work order execution, and production tracking in MES Develop custom scripts (SQL, .NET, JavaScript, XML, JSON) for MES automation IDOCs xml mapping with MES database and custom database Design operator and Supervisor interfaces for MES using Aveva Skelta BPM, System Platform APIs and other framework solutions Provide technical support and troubleshooting for MES applications Work with cross-functional teams to optimize manufacturing processes and ensure system reliability Conduct user training and documentation for MES system usage and best practices Ensure MES system security, compliance, and performance optimization Preferred candidate profile Bachelor's in Computer Science, Industrial Automation, or related field. 58 years in MES implementation, preferably AVEVA MES. Experience in Food & Beverage or Life Sciences. Team management & customer-facing experience. Proficient in AVEVA System Platform, Enterprise Integrator, and Skelta Workflow. Strong knowledge of ISA-95 MES architecture & manufacturing operations. SQL expertise (SQL Server, Oracle) & experience with .NET, JavaScript, XML, JSON. Knowledge of OPC UA/DA, industrial protocols & ERP-MES integration (SAP or similar).

Amdocs helps those who build the future to make it amazing. With our market-leading portfolio of software products and services, we unlock our customers innovative potential, empowering them to provide next-generation communication and media experiences for both the individual end user and enterprise customers. Our employees around the globe are here to accelerate service providers migration to the cloud, enable them to differentiate in the 5G era, and digitalize and automate their operations. Listed on the NASDAQ Global Select Market, Amdocs had revenue of $5.00 billion in fiscal 2024. For more information, visit www.amdocs.com In one sentence We are seeking a Data Engineer with advanced expertise in Databricks SQL, PySpark, Spark SQL, and workflow orchestration using Airflow. The successful candidate will lead critical projects, including migrating SQL Server Stored Procedures to Databricks Notebooks, designing incremental data pipelines, and orchestrating workflows in Azure Databricks What will your job look like Migrate SQL Server Stored Procedures to Databricks Notebooks, leveraging PySpark and Spark SQL for complex transformations. Design, build, and maintain incremental data load pipelines to handle dynamic updates from various sources, ensuring scalability and efficiency. Develop robust data ingestion pipelines to load data into the Databricks Bronze layer from relational databases, APIs, and file systems. Implement incremental data transformation workflows to update silver and gold layer datasets in near real-time, adhering to Delta Lake best practices. Integrate Airflow with Databricks to orchestrate end-to-end workflows, including dependency management, error handling, and scheduling. Understand business and technical requirements, translating them into scalable Databricks solutions. Optimize Spark jobs and queries for performance, scalability, and cost-efficiency in a distributed environment. Implement robust data quality checks, monitoring solutions, and governance frameworks within Databricks. Collaborate with team members on Databricks best practices, reusable solutions, and incremental loading strategies All you need is... Bachelor s degree in computer science, Information Systems, or a related discipline. 4+ years of hands-on experience with Databricks, including expertise in Databricks SQL, PySpark, and Spark SQL. Proven experience in incremental data loading techniques into Databricks, leveraging Delta Lake's features (e.g., time travel, MERGE INTO). Strong understanding of data warehousing concepts, including data partitioning, and indexing for efficient querying. Proficiency in T-SQL and experience in migrating SQL Server Stored Procedures to Databricks. Solid knowledge of Azure Cloud Services, particularly Azure Databricks and Azure Data Lake Storage. Expertise in Airflow integration for workflow orchestration, including designing and managing DAGs. Familiarity with version control systems (e.g., Git) and CI/CD pipelines for data engineering workflows. Excellent analytical and problem-solving skills with a focus on detail-oriented development. Preferred Qualifications Advanced knowledge of Delta Lake optimizations, such as compaction, Z-ordering, and vacuuming. Experience with real-time streaming data pipelines using tools like Kafka or Azure Event Hubs. Familiarity with advanced Airflow features, such as SLA monitoring and external task dependencies. Certifications such as Databricks Certified Associate Developer for Apache Spark or equivalent. Experience in Agile development methodologie Why you will love this job: You will be able to use your specific insights to lead business change on a large scale and drive transformation within our organization. You will be a key member of a global, dynamic and highly collaborative team with various possibilities for personal and professional development. You will have the opportunity to work in multinational environment for the global market leader in its field! We offer a wide range of stellar benefits including health, dental, vision, and life insurance as well as paid time off, sick time, and parental leave!

What you will do In this vital role We are looking for highly motivated expert Senior Data Engineer who can own the design & development of complex data pipelines, solutions and frameworks. The ideal candidate will be responsible to design, develop, and optimize data pipelines, data integration frameworks, and metadata-driven architectures that enable seamless data access and analytics. This role prefers deep expertise in big data processing, distributed computing, data modeling, and governance frameworks to support self-service analytics, AI-driven insights, and enterprise-wide data management. Roles & Responsibilities: Design, develop, and maintain scalable ETL/ELT pipelines to support structured, semi-structured, and unstructured data processing across the Enterprise Data Fabric. Implement real-time and batch data processing solutions, integrating data from multiple sources into a unified, governed data fabric architecture. Optimize big data processing frameworks using Apache Spark, Hadoop, or similar distributed computing technologies to ensure high availability and cost efficiency. Work with metadata management and data lineage tracking tools to enable enterprise-wide data discovery and governance. Ensure data security, compliance, and role-based access control (RBAC) across data environments. Optimize query performance, indexing strategies, partitioning, and caching for large-scale data sets. Develop CI/CD pipelines for automated data pipeline deployments, version control, and monitoring. Implement data virtualization techniques to provide seamless access to data across multiple storage systems. Collaborate with cross-functional teams, including data architects, business analysts, and DevOps teams, to align data engineering strategies with enterprise goals. Stay up to date with emerging data technologies and best practices, ensuring continuous improvement of Enterprise Data Fabric architecture. What we expect of you We are all different, yet we all use our unique contributions to serve patients. Basic Qualifications: Masters degree and 4to 6 years of Computer Science, IT or related field experience OR Bachelors degree and 6 to 8 years of Computer Science, IT or related field experience AWS Certified Data Engineer preferred Databricks Certificate preferred Scaled Agile SAFe certification preferred Preferred Qualifications: Must-Have Skills: Hands-on experience in data engineering technologies such as Databricks, PySpark, SparkSQL Apache Spark, AWS, Python, SQL, and Scaled Agile methodologies. Proficiency in workflow orchestration, performance tuning on big data processing. Strong understanding of AWS services Experience with Data Fabric, Data Mesh, or similar enterprise-wide data architectures. Ability to quickly learn, adapt and apply new technologies Strong problem-solving and analytical skills Excellent communication and collaboration skills Experience with Scaled Agile Framework (SAFe), Agile delivery practices, and DevOps practices. Good-to-Have Skills: Good to have deep expertise in Biotech & Pharma industries Experience in writing APIs to make the data available to the consumers Experienced with SQL/NOSQL database, vector database for large language models Experienced with data modeling and performance tuning for both OLAP and OLTP databases Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops. Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals. Ability to learn quickly, be organized and detail oriented. Strong presentation and public speaking skills.

Extensive experience on Composable Infrastructure such as Liqid or GigaIO Advanced experience with Cisco UCS-X, UCS-C Series infrastructure, UCS Central and Cisco Intersight. Advanced experience with Dell R Series servers and Dell OME Advanced knowledge of Workflow Orchestration platforms, and Container technologies including Kubernetes and Docker. Proficient with BASH, Python, Javascript, Ansible, Terraform, Redfish or similar scripting language. Advanced knowledge in robot framework to automate QA testing and robotic processes. Primary Skills Cisco Certified Network Professional DC (CCNP) Linux Foundation Certified Engineer (LFCE) VMWare Certified Professional (VCP-DCV)

ABOUT AMGEN Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today. ABOUT THE ROLE Role Description: Let’s do this. Let’s change the world. We are looking for highly motivated expert Data Engineer who can own the design, development & maintenance of complex data pipelines, solutions and frameworks. The ideal candidate will be responsible to design, develop, and optimize data pipelines, data integration frameworks, and metadata-driven architectures that enable seamless data access and analytics. This role prefers deep expertise in big data processing, distributed computing, data modeling, and governance frameworks to support self-service analytics, AI-driven insights, and enterprise-wide data management. Roles & Responsibilities: Design, develop, and maintain complex ETL/ELT data pipelines in Databricks using PySpark, Scala, and SQL to process large-scale datasets Understand the biotech/pharma or related domains & build highly efficient data pipelines to migrate and deploy complex data across systems Design and Implement solutions to enable unified data access, governance, and interoperability across hybrid cloud environments Ingest and transform structured and unstructured data from databases (PostgreSQL, MySQL, SQL Server, MongoDB etc.), APIs, logs, event streams, images, pdf, and third-party platforms Ensuring data integrity, accuracy, and consistency through rigorous quality checks and monitoring Expert in data quality, data validation and verification frameworks Innovate, explore and implement new tools and technologies to enhance efficient data processing Proactively identify and implement opportunities to automate tasks and develop reusable frameworks Work in an Agile and Scaled Agile (SAFe) environment, collaborating with cross-functional teams, product owners, and Scrum Masters to deliver incremental value Use JIRA, Confluence, and Agile DevOps tools to manage sprints, backlogs, and user stories. Support continuous improvement, test automation, and DevOps practices in the data engineering lifecycle Collaborate and communicate effectively with the product teams, with cross-functional teams to understand business requirements and translate them into technical solutions Must-Have Skills: Hands-on experience in data engineering technologies such as Databricks, PySpark, SparkSQL Apache Spark, AWS, Python, SQL, and Scaled Agile methodologies. Proficiency in workflow orchestration, performance tuning on big data processing. Strong understanding of AWS services Ability to quickly learn, adapt and apply new technologies Strong problem-solving and analytical skills Excellent communication and teamwork skills Experience with Scaled Agile Framework (SAFe), Agile delivery practices, and DevOps practices. Good-to-Have Skills: Data Engineering experience in Biotechnology or pharma industry Experience in writing APIs to make the data available to the consumers Experienced with SQL/NOSQL database, vector database for large language models Experienced with data modeling and performance tuning for both OLAP and OLTP databases Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops Education and Professional Certifications Minimum 5 to 8 years of Computer Science, IT or related field experience AWS Certified Data Engineer preferred Databricks Certificate preferred Scaled Agile SAFe certification preferred Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals. Ability to learn quickly, be organized and detail oriented. Strong presentation and public speaking skills. EQUAL OPPORTUNITY STATEMENT Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.

Project Role : Application Lead Project Role Description : Lead the effort to design, build and configure applications, acting as the primary point of contact. Must have skills : Apache Airflow Good to have skills : NAMinimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an Application Lead, you will lead the effort to design, build, and configure applications, acting as the primary point of contact. Your typical day will involve collaborating with various teams to ensure that application development aligns with business objectives, overseeing project timelines, and facilitating communication among stakeholders to drive project success. You will also engage in problem-solving activities, ensuring that the applications meet the required standards and functionality while adapting to any changes in project scope or requirements. 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.- Facilitate training and knowledge sharing sessions to enhance team capabilities.- Monitor project progress and implement necessary adjustments to meet deadlines. Professional & Technical Skills: - Must To Have Skills: Proficiency in Apache Airflow.- Good To Have Skills: Experience with cloud platforms such as AWS or Azure.- Strong understanding of workflow orchestration and scheduling.- Experience with data pipeline development and management.- Familiarity with containerization technologies like Docker. Additional Information:- The candidate should have minimum 7.5 years of experience in Apache Airflow.- This position is based at our Bengaluru office.- A 15 years full time education is required. Qualification 15 years full time education

Job Summary: Synechron is seeking an experienced Senior Data Engineer with expertise in AWS, Apache Airflow, and DBT to design and implement scalable, reliable data pipelines. The role involves collaborating with data teams and business stakeholders to develop data solutions that enable actionable insights and support organizational decision-making. The ideal candidate will bring data engineering experience, demonstrating strong technical skills, strategic thinking, and the ability to work in a fast-paced, evolving environment. Software Requirements: Required: Strong proficiency in AWS services including S3, Redshift, Lambda, and Glue, with proven hands-on experience Expertise in Apache Airflow for workflow orchestration and pipeline management Extensive experience with DBT for data transformation and modeling Solid knowledge of SQL for data querying and manipulation Preferred: Familiarity with Hadoop, Spark, or other big data technologies Experience with NoSQL databases (e.g., DynamoDB, Cassandra) Knowledge of data governance and security best practices within cloud environments Overall Responsibilities: Lead the design, development, and maintenance of scalable and efficient data pipelines and workflows utilizing AWS, Airflow, and DBT Collaborate with data scientists, analysts, and business teams to gather requirements and translate them into technical solutions Optimize Extract, Transform, Load (ETL) processes to enhance data quality, integrity, and timeliness Monitor pipeline performance, troubleshoot issues, and implement improvements to ensure operational excellence Enforce data management, governance, and security protocols across all data flows Mentor junior data engineers and promote best practices within the team Stay current with emerging data technologies and industry trends, recommending innovations for the data ecosystem Technical Skills (By Category): Programming Languages: Essential: SQL, Python (preferred for scripting and automation) Preferred: Spark, Scala, Java (for big data integration) Databases/Data Management: Extensive experience with data warehousing (Redshift, Snowflake, or similar) and relational databases (MySQL, PostgreSQL) Familiarity with NoSQL databases such as DynamoDB or Cassandra is a plus Cloud Technologies: AWS cloud platform, leveraging services like S3, Lambda, Glue, Redshift, and IAM security features Frameworks and Libraries: Apache Airflow, dbt, and related data orchestration and transformation tools Development Tools and Methodologies: Git, Jenkins, CI/CD pipelines, Agile/Scrum environment experience Security Protocols: Knowledge of data encryption, access control, and compliance standards in cloud data engineering Experience Requirements: At least 8 years of professional experience in data engineering or related roles with a focus on cloud ecosystems and big data pipelines Demonstrated experience designing and managing end-to-end data workflows in AWS environments Proven success in collaborating with cross-functional teams and translating business requirements into technical solutions Prior experience mentoring junior engineers and leading data projects is highly desirable Day-to-Day Activities: Develop, deploy, and monitor scalable data pipelines using AWS, Airflow, and DBT Collaborate regularly with data scientists, analysts, and business stakeholders to refine data requirements and deliver impactful solutions Troubleshoot production data pipeline issues to resolve data quality or performance bottlenecks Conduct code reviews, optimize existing workflows, and implement automation to improve efficiency Document data architecture, pipelines, and governance practices for knowledge sharing and compliance Keep abreast of emerging data tools and industry best practices, proposing enhancements to existing systems Qualifications: Bachelor’s degree in Computer Science, Data Science, Engineering, or related field; Master’s degree preferred Professional certifications such as AWS Certified Data Analytics – Specialty or related credentials are advantageous Commitment to continuous professional development and staying current with industry trends Professional Competencies: Strong analytical, problem-solving, and critical thinking skills Excellent communication abilities to effectively liaise with technical and business teams Proven leadership in mentoring team members and managing project deliverables Ability to work independently, prioritize tasks, and adapt to changing business needs Innovative mindset focused on scalable, efficient, and sustainable data solutions

ABOUT AMGEN Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today. ABOUT THE ROLE Role Description: Let’s do this. Let’s change the world. We are looking for highly motivated expert Data Engineer who can own the design & development of complex data pipelines, solutions and frameworks. The ideal candidate will be responsible to design, develop, and optimize data pipelines, data integration frameworks, and metadata-driven architectures that enable seamless data access and analytics. This role prefers deep expertise in big data processing, distributed computing, data modeling, and governance frameworks to support self-service analytics, AI-driven insights, and enterprise-wide data management. Roles & Responsibilities: Design, develop, and maintain complex ETL/ELT data pipelines in Databricks using PySpark, Scala, and SQL to process large-scale datasets Understand the biotech/pharma or related domains & build highly efficient data pipelines to migrate and deploy complex data across systems Design and Implement solutions to enable unified data access, governance, and interoperability across hybrid cloud environments Ingest and transform structured and unstructured data from databases (PostgreSQL, MySQL, SQL Server, MongoDB etc.), APIs, logs, event streams, images, pdf, and third-party platforms Ensuring data integrity, accuracy, and consistency through rigorous quality checks and monitoring Expert in data quality, data validation and verification frameworks Innovate, explore and implement new tools and technologies to enhance efficient data processing Proactively identify and implement opportunities to automate tasks and develop reusable frameworks Work in an Agile and Scaled Agile (SAFe) environment, collaborating with cross-functional teams, product owners, and Scrum Masters to deliver incremental value Use JIRA, Confluence, and Agile DevOps tools to manage sprints, backlogs, and user stories. Support continuous improvement, test automation, and DevOps practices in the data engineering lifecycle Collaborate and communicate effectively with the product teams, with cross-functional teams to understand business requirements and translate them into technical solutions Must-Have Skills: Hands-on experience in data engineering technologies such as Databricks, PySpark, SparkSQL Apache Spark, AWS, Python, SQL, and Scaled Agile methodologies. Proficiency in workflow orchestration, performance tuning on big data processing. Strong understanding of AWS services Ability to quickly learn, adapt and apply new technologies Strong problem-solving and analytical skills Excellent communication and teamwork skills Experience with Scaled Agile Framework (SAFe), Agile delivery practices, and DevOps practices. Good-to-Have Skills: Data Engineering experience in Biotechnology or pharma industry Experience in writing APIs to make the data available to the consumers Experienced with SQL/NOSQL database, vector database for large language models Experienced with data modeling and performance tuning for both OLAP and OLTP databases Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops Education and Professional Certifications Any Degree and 6-8 years of experience AWS Certified Data Engineer preferred Databricks Certificate preferred Scaled Agile SAFe certification preferred Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals. Ability to learn quickly, be organized and detail oriented. Strong presentation and public speaking skills. EQUAL OPPORTUNITY STATEMENT Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.

ABOUT AMGEN Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today. ABOUT THE ROLE Role Description: Let’s do this. Let’s change the world. We are looking for highly motivated expert Data Engineer who can own the design & development of complex data pipelines, solutions and frameworks. The ideal candidate will be responsible to design, develop, and maintain data pipelines, data integration frameworks, and metadata-driven architectures that enable seamless data access and analytics. This role prefers deep expertise in big data processing, distributed computing, data modeling, and governance frameworks to support self-service analytics, AI-driven insights, and enterprise-wide data management. Roles & Responsibilities: Design, develop, and maintain complex ETL/ELT data pipelines in Databricks using PySpark, Scala, and SQL to process large-scale datasets Understand the biotech/pharma or related domains & build highly efficient data pipelines to migrate and deploy complex data across systems Design and Implement solutions to enable unified data access, governance, and interoperability across hybrid cloud environments Ingest and transform structured and unstructured data from databases (PostgreSQL, MySQL, SQL Server, MongoDB etc.), APIs, logs, event streams, images, pdf, and third-party platforms Ensuring data integrity, accuracy, and consistency through rigorous quality checks and monitoring Expert in data quality, data validation and verification frameworks Innovate, explore and implement new tools and technologies to enhance efficient data processing Proactively identify and implement opportunities to automate tasks and develop reusable frameworks Work in an Agile and Scaled Agile (SAFe) environment, collaborating with cross-functional teams, product owners, and Scrum Masters to deliver incremental value Use JIRA, Confluence, and Agile DevOps tools to manage sprints, backlogs, and user stories. Support continuous improvement, test automation, and DevOps practices in the data engineering lifecycle Collaborate and communicate effectively with the product teams, with cross-functional teams to understand business requirements and translate them into technical solutions Must-Have Skills: Hands-on experience in data engineering technologies such as Databricks, PySpark, SparkSQL Apache Spark, AWS, Python, SQL, and Scaled Agile methodologies. Proficiency in workflow orchestration, performance tuning on big data processing. Strong understanding of AWS services Ability to quickly learn, adapt and apply new technologies Strong problem-solving and analytical skills Excellent communication and teamwork skills Experience with Scaled Agile Framework (SAFe), Agile delivery practices, and DevOps practices. Good-to-Have Skills: Data Engineering experience in Biotechnology or pharma industry Experience in writing APIs to make the data available to the consumers Experienced with SQL/NOSQL database, vector database for large language models Experienced with data modeling and performance tuning for both OLAP and OLTP databases Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops Education and Professional Certifications Minimum 5 to 8 years of Computer Science, IT or related field experience AWS Certified Data Engineer preferred Databricks Certificate preferred Scaled Agile SAFe certification preferred Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals. Ability to learn quickly, be organized and detail oriented. Strong presentation and public speaking skills. EQUAL OPPORTUNITY STATEMENT Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.