Takeda is advancing an exciting product pipeline and wants to ensure that we have the infrastructure and talent in place to support it. Our overall goal is to get our therapeutics to patients safely and quickly via an optimized operational model and integrated clinical data pipeline.
The REMOTE based Data Engineer will work directly with architects and product owners on the delivery of data pipelines and platforms for structured and unstructured data as part of a transformational data program. This data program will include an integrated data flow with end-to end control of data, internalization of numerous systems and processes, broad enablement of automation and near-time data access, efficient data review and query, and enablement of disruptive technologies for next-generation trial designs and insight derivation.
As a Data Engineer you will:
Provide leadership to to develop and execute highly complex and large-scale data structures and pipelines to organize, collect and standardize data to generate insights and addresses reporting needs.
Interpret and integrate advanced techniques to ingest structured and unstructured data across complex ecosystem
Delivery & Business Accountabilities:
Build and maintain technical solutions required for optimal ingestion, transformation, and loading of data from a wide variety of data sources and large, complex data sets with a focus on clinical and operational data
Develop data profiling and data quality methodologies and embed them into the processes involved in transforming data across the systems.
Manages and influences the data pipeline and analysis approaches, uses different technologies, big data preparations, programming and loading as well as initial exploration in the process of searching and finding data patterns.
Uses data science input and requests, translates these from data exploration - large record (billions) and unstructured data sets - to mathematic algorithms and uses various tooling from programming languages to new tools (artificial and machine learning) to find data patterns, build and optimize models.
Leads and implements ongoing tests in the search for solutions in data modelling, collects and prepares the training of data, tunes the data, optimizes algorithm implementations to test, scale, and deploy future models.
Conducts and facilitates analytical assessment conceptualizing business needs and translates them into analytical opportunities.
Leads the development of technical roadmaps and approaches for data analyses to find patterns, to design data models, to scale the model to a managed production environment within the current or a technical landscape to develop.
Influences and manages data exploration from analysis to scalable models, works independently and decides quickly on transfers in complex data analysis and modelling.
CORE ELEMENTS RELATED TO THIS ROLE:
DIMENSIONS AND ASPECTS:
Technical/Functional (Line) Expertise:
Inspire, motivate, and drive results
Effectively communicate ideas and data verbally and in writing
Decision-making and Autonomy:
Provide input to highly complex decisions that impact overall R&D
Seek input from multiple constituents and stakeholders to drive innovative solutions
Incorporate feedback and ensure decisions are implemented swiftly to yield flawless execution
Recommend, influence and implement organizational change and innovation
Identify opportunities and anticipate changes in the business landscape through an understanding and ongoing assessment of the environment affecting the business.
Serve as a role model, demonstrating respect and inclusion, creating a culture that fosters innovation
Navigate in a global ecosystem (internal and external) with a high degree of complexity
Recognize and understand broader, enterprise level perspective
EDUCATION, BEHAVIOURAL COMPETENCIES AND SKILLS:
Bachelor's degree or higher in a quantitative discipline such as Statistics, Mathematics, Engineering, Computer Science, Econometrics or information sciences such as business analytics or informatics
5+ years of experience working in data engineering role in an enterprise environment
Strong experience with ETL/ELT design and implementations in the context of large, disparate and complex datasets
Demonstrated experience with a variety of relational database and data warehousing technology such as AWS Redshift, Athena, RDS, BigQuery
Demonstrated experience with big data processing systems and distributed computing technology such as Databricks, Spark, Sagemaker, Kafka, etc.
Experience with developing solutions on cloud computing services and infrastructure in the data and analytics space
Solution-oriented enabler mindset
Prior experience with Data Engineering projects and teams at an Enterprise level
Location and Salary Information:
- In accordance with the CO Equal Pay Act, Colorado Applicants Are Not Permitted to Apply.
- Base Salary Range: $ 102,200 - $146,000 based on candidate professional experience level. Employees may also be eligible for Short Term and Long-Term Incentive benefits as well. Employees are eligible to participate in Medical, Dental, Vision, Life Insurance, 401(k), Charitable Contribution Match, Holidays, Personal Days & Vacation, Tuition Reimbursement Program and Paid Volunteer Time Off.
- This posting is made in compliance with Colorado's Equal Pay for Equal Work Act, C.R.S. § 8-5-101 et seq.
- .This position is currently classified as REMOTE in accordance with Takeda's Hybrid and Remote Work policy.
Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, status as a Vietnam era veteran, special disabled veteran, or other protected veteran in accordance with applicable federal, state and local laws, and any other characteristic protected by law. Locations
Massachusetts - Virtual Worker Type
Employee Worker Sub-Type
Regular Time Type