Data Engineer III

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

When your part of the team at Thermo Fisher Scientific, you’ll do important work, like helping customers in finding cures for cancer, protecting the environment or making sure our food is safe. Your work will have real-world impact, and you’ll be supported in achieving your career goals.

Location/Division Specific Information

Data Engineer III, based out of our Bangalore location, plays a key role in Enterprise Data Platform (EDP) Operations organization providing business continuity for critical business processes, IT systems and IT solutions through project implementations, enhancements, documentation and operational support.

How will you make an impact?

Being part of an organization that provides analytics driven data solutions for all businesses across Thermo Fisher Scientific, you will be instrumental in helping our business partners and customers with their data and analytics needs.

What will you do?

• Own and deliver enhancements associated with Data platform solutions.
• Maintains and Enhances scalable data pipelines and builds out new API integrations to support continuing increases in data volume and complexity.
• Enhance/Support solutions using Pyspark/EMR, SQL and databases, AWS Athena, S3, Redshift, AWS API Gateway, Lambda, Glue and other Data Engineering technologies.
• Write Complex Queries and edit them as required for implementing ETL/Data solutions.
• Measure performance and environment of application with system & application log tools and act to improve accordingly.
• Implement solutions using AWS and other cloud platform tools, including GitHub, Jenkins, Terraform, Jira, and Confluence.
• Follow agile development methodologies to deliver solutions and product features by following DevOps, Data Ops and Dev Sec Ops practices.
• Propose Data load optimizations and continuously implement to improve the performance of the Data loads
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Keep the data separated and secure across through multiple data centers and AWS regions.
• Be available and participate in on-call schedule to address critical operational incidents and business requests

How will you get here?

• Bachelor’s degree in Computer Science with at least 5 years of Data Engineering experience using AWS services, Pyspark/EMR.
• Having Certifications like AWS Certified Data Analytics, CCA Spark and Hadoop Developer or CCP Data Engineer is highly desirable.

Experience & Skills:

• 8+ Years of Experience in Data Lake, Data Analytics & Business Intelligence Solutionsand at least 3+ as AWS Data Engineer
• Full life cycle project implementation experience in AWS using Pyspark/EMR, Athena, S3, Redshift, AWS API Gateway, Lambda, Glue and other managed services
• Strong experience in building ETL data pipelines using Pyspark on EMR framework
• Hands on experience in using S3, AWS Glue jobs, S3 Copy, Lambda and API Gateway.
• Working SQL experience to troubleshoot SQL code. Redshift knowledge is an added advantage.
• Strong experience in DevOps and CI/CD using Git and Jenkins, experience in cloud native scripting such as CloudFormation and ARM templates
• Hands-on with system & application log tools like Datadog, CloudWatch, Splunk etc.
• Experience working with Python, Python ML libraries for data analysis, wrangling and insights generation
• Experience using Jira for task prioritization and Confluence and other tools for documentation.
• Experience in Python and common python libraries.???
• Strong analytical experience with database in writing complex queries, query optimization, debugging, user defined functions, views, indexes etc.??
• Experience with source control systems such as Git, Bitbucket, and Jenkins build and continuous integration tools.??
• Strong understanding of AWS Data lake and data bricks.
• Exposure to Kafka, Redshift, Sage Maker would be added advantage
• Exposure to data visualization tools like Power BI, Tableau etc.
• Functional Knowledge in the areas of Sales & Distribution, Material Management, Finance and Production Planning is preferred

Knowledge, Skills, Abilities

• Full life cycle implementation experience in AWS using Pyspark/EMR, Athena, S3, Redshift, AWS API Gateway, Lambda, Glue and other managed services
• Experience with agile development methodologies by following DevOps, Data Ops and Dev Sec Ops practices.
• Manage life cycle of ETL Pipelines and other cloud platform tools, including GitHub, Jenkins, Terraform, Jira, and Confluence.
• Excellent written, verbal and inter-personal and stakeholder communication skills.
• Ability to analyze trends associated with huge datasets.
• Ability to work with cross functional teams from multiple regions/ time zones by effectively leveraging multi-form communication (Email, MS Teams for voice and chat, meetings)
• Excellent prioritization and problem-solving skills.
• Action Oriented: Have a sense of urgency, high energy and enthusiasm in managing Systems and Platforms
• Drives Results: Consistently achieving results, even under tough circumstances.
• Global Perspective: Takes a broad view when approaching issues; using a global lens.
• Learn and train other team members
• Communicates Effectively: Provide timely and consistent updates and recommendations on BI Operational issues and improvements to stakeholders.
• Drive to meet and exceed BI Operational SLAs for Service Now incidents, Major Incidents, xMatters alerts, Employee Experience Metrics and BI application /process availability metrics.