TE Connectivity
Sr. Data Engineer
Job Description
Job Overview
Responsible for designing and establishing the solution architecture for analytical platforms and/or data-enabled solutions.Has broad understanding of the entire data and analytics eco-system of tools and technologies, with hands-on experience across all three core data domains of data science, data engineering, and data visualization. Responsible for fleshing out the details of the end-to-end component architecture being implemented by the team. Contributes to the team’s development velocity, if necessary. Understands how an organization’s data platform integrates within the overall technical architecture. Understands the business purpose the role fulfills, and the roadmap for the lifecycle of an organization’s systems. Sets the direction and establishes the approach for integrating information applications and programs.
Corporate Procurement Business Analytics team is responsible for providing insights to business data in areas like sourcing, procurement and supply chain. Building data landscape, develop user friendly reports and analytics tools and platforms for management and users.
Job Responsibilities
As a Data Engineer, you will play a key role in developing the infrastructure needed to support the company’s data operations. You will be responsible for designing, building, and maintaining the systems that ensure data is accessible, reliable, and secure. This includes the creation and management of data pipelines and storage solutions, ensuring high data quality, and collaborating with various teams to meet data needs for analytics and business intelligence.
- Develop and maintain data pipelines for efficient extraction, transformation, and loading (ETL) processes.
- Design and optimize data storage solutions, including Amazon Redshift data warehouses and Amazon S3 data lakes
- Ensure data quality and integrity through validation, cleansing, and error handling processes.
- Collaborate with data analysts, data architects, and software engineers to understand data requirements and deliver relevant data sets for business intelligence.
- Implement data security measures and access controls to protect sensitive information.
- Automate and improve data processes and workflows for scalability and efficiency.
- Monitor data infrastructure performance and address any issues promptly.
- Stay updated on industry trends and emerging technologies in data engineering.
- Document data pipelines, processes, and best practices to facilitate knowledge sharing.
- Continuously optimize data architecture to support the company’s evolving data needs.
- Work cross-functionally to drive data-driven decision-making within the organization.
Job Requirements
- Bachelor’s degree in Computer Science, Information Technology.
- Minimum 6 years of experience in data engineering
- Knowledge of AWS services, particularly Glue, Redshift and S3.
- Data Storage and Management – Amazon S3, Amazon RDS and DynamoDB
- Data Processing and ETL – AWS Glue
- Data Warehousing – Amazon Redshift
- Programming and Scripting:
- Proficiency in languages like Python, Java, or Scala for data manipulation and automation.
- Data Modeling and Architecture
- Monitoring and Optimization – Using AWS CloudWatch for monitoring and optimizing data workflows
- Proficiency in SQL and database management.
- Experience with ETL (Extract, Transform, Load) processes.
- Familiarity with data warehousing and cloud platforms (AWS, Azure, or Google Cloud).
- Strong data modeling skills.
Core Expertise: AWS, Data Warehousing, Data Quality, Data Security, Collaboration, Documentation, SQL Proficiency, ETL Expertise, Data Modeling
Competencies
Values: Integrity, Accountability, Inclusion, Innovation, Teamwork
