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 MapReduce (EMR)
Neptune
ElastiCache
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 them. Examples include: ETL/ELT, data vault and data warehousing techniques, normalization/de-normalization, key-value, in-memory, wide column, columnar, graph, text-indexing, vector, partitioning, streaming, and message queuing
- Experienced with medallion architecture providing progressive data cleansing, deduplication, and applied data quality through bronze, silver, and gold layers.
- Strong software engineering and object-oriented programming skills with expertise in SQL, Python, Scala, R, and Java; including open-source frameworks/libraries, such as Spark, Airflow and streaming services.
- Working knowledge of traditional big data systems, such as Hadoop, Impala, Sqoop, Oozie, Cassandra, Redshift, Oracle, MS SQL Server, and PostgreSQL.
- Experience with varying file and table data formats such as ORC, Parquet, Delta, and Iceberg.
- Hands-on experience with various Business Intelligence tools such as Tableau and PowerBI
Leadership and Teamwork
- Strong track record of effective cross-functional team collaboration and execution
- Experience working in multi-cultural and international environments
- Ready to think, behave, and act in an innovative consulting manner to drive the GDBT Technology Strategy.
- Effective leadership skills. These include team building, consensus building, the ability to balance team and individual responsibilities and achieving goals through others not directly under the leader's supervision, by working ethically and with integrity.
- Communication, Organization, and Issue Resolution Skills
- Excellent interpersonal and communication skills. Influential networker with a collaborative mindset and strong customer-centric focus.
- Ability to plan, organize, prioritize, and work effectively in a fast paced and dynamic environment.
- Proven problem solver who takes ownership and is driven by a strong sense of urgency, timely resolution, and keen attention to detail to execute successfully under time and resource demands.
- Information Technology Planning, Analysis, Design, Architecture and Management
- Strong business analysis skills and experience, which include issues resolution and business needs solutioning.
- Familiarity with information management practices, system development life cycle (SDLC) management, IT services management, agile and lean methodologies, infrastructure and operations, Enterprise Architecture (EA), and Information Technology Infrastructure Library (ITIL) frameworks.
- Experience in managing application / system changes in accordance with computer system validation, 21 CFR Part 11 and GxP regulations.
Domain Knowledge
- Experience in enabling product development through the use of big data analytics and data science solutions and familiarity of pharma functions and processes.
- Strong technical knowledge of life science production systems that will help weigh trade-offs and evaluate risks when designing for future states.
Eisai Core Values
- Embodies and consistently demonstrates Eisai’s core company values: Quality, Teamwork, Respect, Integrity, and Professionalism.