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 Solutions and 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.
Thermo Fisher Scientific is an EEO/Affirmative Action Employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other legally protected status.
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