21 Dec
TE Connectivity

21 Dec

TE Connectivity


Job Description

At TE we strongly believe that data and analytics are strategic drivers for future success. We are building a world class advanced analytics team that will solve some of the most complex strategic problems and deliver topline growth and operational efficiencies across our business The Analytics team at TE is part of the TE Information Solutions (TEIS) Organization and is responsible for driving organic growth by leveraging big data and advanced analytics. The team reports to the VP and Chief Data Officer at TEIS, works closely with the SVP of Corporate Strategy, and has regular interactions with the companys C-Suite.

We are on an exciting journey to build and scale our advanced analytics practice.

TE is looking for a Cloud Data Engineer. The suitable candidate should have demonstrated experience in designing and implementing ETL solutions on-premise and cloud platforms to support Enterprise data warehouse, Data Lake and advanced analytics capabilities. Success in this role comes from marrying a strong data engineering background with product and business acumen to deliver scalable data pipeline and BI solutions that can enable data for Self Service and Advanced Analytics at TE in a simple and standard manner.

Primary Responsibilities

Design and develop ETL solutions using data warehouse design best practices for the Next-Generation Analytics platform on Big Data.

Analyze data requirements, complex source data, data models, and determine the best methods in extracting, transforming, and loading the data into the data staging, warehouse, and other system integration projects.

Document all ETL and data warehouse processes and flows.

Develop and deploy ETL job workflow with reliable error/exception handling and rollback.

Design, Develop, Test, Adapt ETL code & jobs to accommodate changes in source data and new business requirements.

Manage foundational data administration tasks such as scheduling jobs, troubleshooting job errors, identifying issues with job windows, assisting with Database backups and performance tuning.

Ensure data quality throughout the entire ETL process, including audits and feedback loops to sources of truth.

Create or update technical documentation for transition to support teams.

Develop, contribute, and adhere to the development of standards and sound procedural practices.

Required Skills

2 years of Data Engineering experience in ETL design, development, optimization & testing using Talend on database like Oracle, HANA, Redshift, Aurora, etc.

2 years of PL/SQL, Complex SQL Tuning, Stored Procedures, Data Warehousing best practices experience

1 years of experience with AWS Services such as S3, Glue, EMR, Aurora, Redshift

1 years of experience in relational and Cloud database design, optimization, and performance; preferably with AWS Redshift, SAP HANA, BW, Oracle, and Hadoop

1 years of experience in Spark for developing flows using Batch, Realtime and Streaming processes

Solid understanding of ETL pipeline and workflow managements tools such as AWS Glue, AWS Kinesis, AWS App Flow, AWS Step Functions, etc.

Proficiency with modern software development methodologies such as Agile, source control, CI/CD, project management and issue tracking with JIRA

Experience in a life sciences research environment a plus

Strong problem-solving capabilities. Results oriented. Relies on fact-based logic for decision-making.

Ability to work with multiple projects and work streams at one time. Must be able to deliver results based upon project deadlines.

Willing to flex daily work schedule to allow for time-zone differences for global team communications

Strong interpersonal and communication skills

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