Data Engineering Manager
5 days ago
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Job DescriptionThe Future Begins Here
At Takeda, we are leading digital evolution and global transformation. By building innovative solutions and future-ready capabilities, we are meeting the needs of patients, our people, and the planet.
Bengaluru has been selected to be home to Takeda's recently launched Innovation Capability Center thanks to its international recognition in qualified and experienced talent in the data, digital, and technology fields. We invite you to join our digital transformation journey.
In this role, you will have the opportunity to boost your skills and become the heart of an innovative engine that is contributing to global impact and improvement.
At Takeda's ICC We Unite in DiversityTakeda is committed to creating an inclusive and collaborative workplace, where individuals are recognized for the backgrounds and abilities they bring to our company. We are continuously improving our collaborators' journey in Takeda, and we welcome applications from all qualified candidates. Here, you will feel welcomed, respected, and valued as an important contributor to our diverse team.
The OpportunityAs a Data Engineer, you will support data operations and ETL workflows, ensuring robust data pipelines and reliable analytics environments. You will work closely with cross-functional teams to maintain data quality, troubleshoot issues, and enable data-driven decision-making across the organization.
Operational Leadership
• Own end-to-end health of Databricks, Informatica, and Airflow environments used for commercial data operations.
• Monitor daily pipeline performance and drive MTTA / MTTR improvements through automation and proactive analysis.
• Oversee incident response, RCA documentation, and recurring issue elimination.
• Maintain and evolve operational dashboards and SLA tracking metrics.
• Review and approve all production change requests and deployments.
• Maintain pipelines that meet business needs, adhere to Takeda standards, and incorporate best practices exploiting the benefits of cloud-nativity
• Lead technical solution reviews with stakeholders
• Directly support or coordinate with the help of DD&T SMEs complex data challenges to find fit-for-purpose solutions
• Take full accountability of data products and help plan, mature, and support for ongoing operation of KPI's for quality and availability
• Work with DevOps teams to operationalize data products and help in troubleshooting when needed
People & Process Management
• Lead and mentor a team of 4–8 DataOps Engineers (Databricks + ETL + Airflow).
• Establish 24x7 monitoring coverage, on-call rotation, and escalation protocols.
• Drive standardization via runbooks, RCA templates, and knowledge bases.
• Define KPIs such as SLA adherence, job success rate, MTTA, MTTR, and recurring issue trend reduction.
• Advise, consult, mentor and coach other data and analytic professionals
Cross-Functional Collaboration
• Partner with data architects, analysts, and business owners to ensure operational readiness of new data pipelines.
• Collaborate with CloudOps, Security, and Platform Engineering on system reliability and cost optimization.
• Serve as the primary contact for incident communications to business stakeholders.
Continuous Improvement & Automation
• Identify repetitive manual tasks and partner with engineers to automate them (e.g., job restarts, data validations, alerts).
• Promote best practices for observability, cost governance, and data quality monitoring.
• Analyze production metrics and recommend processes or tool improvements.
• Help adopt changes in solutioning and ways of working
• Stay current with relevant data providers and technology trends Key Skills & Competencies
Databricks Operations
Working knowledge of clusters, jobs, workflows, and Delta Lake; able to guide troubleshooting and optimizations.
ETL Platform Management
Experienced in managing Informatica (BDM/IICS) operations at scale.
Workflow Orchestration
Familiarity with Airflow DAGs, dependencies, and failure handling.
Operational Metrics
Strong understanding of MTTA, MTTR, SLA adherence, and trend reporting.
Incident & Problem Management
Leads RCA reviews; ensures lessons learned are acted upon.
Leadership
Coaches engineers on structured problem-solving and incident ownership.
Communication
Effective communicator with both technical and business stakeholders; translates incidents into business terms.
Domain Knowledge (Nice to Have)
Understanding of Pharma commercial data flows (Sales, CRM, MDM, IQVIA feeds).
Experience Profile• 8–12 years of total experience in Data Operations / Data Engineering.
• Minimum 2–3 years managing production data environments (Databricks, ETL, or Cloud Data Ops).
• Proven track record of reducing MTTR, increasing job success rates, and improving operational maturity.
• Prior experience in Pharma or Life Sciences preferred.
BENEFITS:
It is our priority to provide competitive compensation and a benefit package that bridges your personal life with your professional career. Amongst our benefits are:
- Shift Timing: 3:00 PM – 12:00 AM IST
- Company-Provided Transport: Available at scheduled times for 2nd shift employees for a smooth commute to office and back home
- Security Escort for Drop-Off: Female employees receive a security escort to their designated drop-off point after the shift for safety
- Shift Allowance: Additional shift allowance will be provided for hours worked outside regular working hours
- Food/Meal: Meal will be provided for the 2nd shift employees
- Competitive Salary + Performance Annual Bonus
- Flexible work environment, including hybrid working
- Comprehensive Healthcare Insurance Plans for self, spouse, and children
- Group Term Life Insurance and Group Accident Insurance programs
- Employee Assistance Program
- Broad Variety of learning platforms
- Diversity, Equity, and Inclusion Programs
- Reimbursements – Home Internet & Mobile Phone
- Employee Referral Program
- Leaves – Paternity Leave (4 Weeks) , Maternity Leave (up to 26 weeks), Bereavement Leave (5 calendar days)
#Li-Hybrid
LocationsIND - BengaluruWorker TypeEmployeeWorker Sub-TypeRegularTime TypeFull time-
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