Senior Data Engineer

Job Summary
The Global Data Engineering Lead (GDEL/Senior Engineer) – Data & Analytics, will work to lead multiple initiatives, solutions, and teams within Eisai’s Global Data & Analytics technology organization within our GDASC. Reporting directly to the Global Data & Analytics Technology Lead, this role contributes to the overall mission of establishing future-proof data and solution architectures supporting data engineering, data science, analytics, business intelligence, and AI globally.

The GDEL will work collaboratively with global GDBT leaders and peers, business stakeholders, consultants, technology vendors, and managed service providers to deliver successful technical projects that meet complex business requirements providing a cohesive and unified data strategy and implementation.

They are responsible for the co-creation, architecture, design, development, and implementation of data analytics, AI architecture, and reference frameworks supporting Eisai’s global businesses. They will lead and be responsible for participating in the strategic planning and hands-on engineering of solutions and cloud environments that support advanced analytics, data science, AI, and other data platform initiatives. This will include supporting commercial, R&D, and corporate analysis initiatives as well as the associated personas such as enterprise users, data analysts, data scientists, data engineers, and AI engineers.

Deep experience required with Eisai’s Data Foundational Platforms which are Databricks, Informatica and Tableau.

Essential Functions
Inspires, leads, and directs the GDASC technical data & analytics teams to promote the capabilities and adoption of business intelligence, analytics, and AI solutions supporting Eisai globally.
Should have the ability to perform “hands-on” work participating in the build of data & analytics solutions within Eisai’s ecosystem of tools.
Manages, advises, and coaches team members within the GDASC.
Works with Global D&A leadership to support enterprise operating models for data and analytics for both global and federated capabilities and how they interact. The goal is an effective, efficient, scalable, and agile model driving value from standardization and reuse of advanced capabilities while supporting regionally relevant flexibility and delivery autonomy.
Coaches and mentors operational support teams on technical concepts, designs, and system functionality to support ongoing projects as well as projects in production.
As a technology strategist, they contribute to the Data and Analytics business strategy.
Works collaboratively across the global organization to build the data ingestion, storage and/or virtualization structures needed to support our next generation of data products, self-service analytics, and data democratization initiatives.
Should enable operational efficiency and effectiveness providing governed data democratization as an output.

Requirements

Work Experience and Education
An undergraduate or postgraduate degree in computer science, information science, management information systems, a related field, or equivalent experience relevant to this position.
10+ years experience working with structured, semi-structured, and unstructured data.
10+ years IT domain experience in pharmaceutical industry preferred but not required.
8+ years experience designing and implementing data solutions on Amazon Web Services (AWS), incorporating product offerings such as:
Athena
Lambda Functions
DynamoDB
Managed Airflow (MWAA)
EC2
Managed Kafka (MSK)
Elastic Map Reduce (EMR)
Neptune
Elasti Cache
RDS – Aurora PostgreSQL
Glue
Redshift
Kinesis
S3 Standard, Glacier, etc.
5+ years experience using data management and analysis tools including Databricks, Informatica, RStudio/Posit, and Immuta.
Strong knowledge of data wrangling, preparation, and ETL for use in advanced analytics, machine learning and AI.
Deeply passionate about learning and innovating using leading edge and next generation solutions in big data engineering, cloud, and open source.
Strong data architecture, warehousing, modeling and wrangling skills demonstrating an understanding of various data architecture patterns and when to use…