Data Engineer - ETL (3-7 yrs)

As a Senior Data Engineer, you will be responsible for building and supporting large-scale data architectures that provide information to downstream systems and business users. We are seeking an innovative and experienced individual who can aggregate and organize data from multiple sources to streamline business decision-making.

In your role, you will collaborate closely with Data Engineer Leads and partners to establish and maintain data platforms that support front-end analytics. Your contributions will inform Takeda's dashboards and reporting, providing insights to stakeholders throughout the business.

How you will contribute :

- Develop and maintain scalable data pipelines, in line with ETL principles, and build out new integrations, using AWS native technologies, to support continuing increases in data source, volume, and complexity.

- Define data requirements, gather, and mine data, while validating the efficiency of data tools in the Big Data Environment.

- Lead the evaluation, implementation and deployment of emerging tools and processes to improve productivity.

- Implement processes and systems to provide accurate and available data to key stakeholders, downstream systems, and business processes.

- Partner with Business Analytics and Solution Architects to develop technical architectures for strategic enterprise projects and initiatives.

- Coordinate with Data Scientists to understand data requirements, and design solutions that enable advanced analytics, machine learning, and predictive modelling.

- Mentor and coach junior Data Engineers on data standards and practices, promoting the values of learning and growth.

- Foster a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions.

Minimum Requirements/Qualifications :

- Bachelor's degree in Engineering, Computer Science, Data Science, or related field

- 3+ years of experience in software development, data science, data engineering, ETL, and analytics reporting development

- Experience designing, building, implementing, and maintaining data and system integrations using dimensional data modelling and development and optimization of ETL pipelines

- Proven track record of designing and implementing complex data solutions

- Demonstrated understanding and experience using:

- Data Engineering Programming Languages (i.e., Python)

- Distributed Data Technologies (e.g., Pyspark)

- Cloud platform deployment and tools (e.g., Kubernetes)

- Relational SQL databases

- DevOps and continuous integration

- AWS cloud services and technologies (i.e., Lambda, S3, DMS, Step Functions, Event Bridge, Cloud Watch, RDS)

- Databricks/ETL

- IICS/DMS

- GitHub

- Event Bridge, Tidal

- Understanding of database architecture and administration

- Utilizes the principles of continuous integration and delivery to automate the deployment of code changes to elevate environments, fostering enhanced code quality, test coverage, and automation of resilient test cases

- Processes high proficiency in code programming languages (e.g., SQL, Python, Pyspark, AWS services) to design, maintain, and optimize data architecture/pipelines that fit business goals

- Strong organizational skills with the ability to manage multiple projects simultaneously and operate as a leading member across globally distributed teams to deliver high-quality services and solutions

- Excellent written and verbal communication skills, including storytelling and interacting effectively with multifunctional teams and other strategic partners

- Strong problem solving and troubleshooting skills

- Ability to work in a fast-paced environment and adapt to changing business priorities