Senior Data Engineer
Precision Medicine Group
IndiaremotePosted 23 days ago
Skill Required
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Key highlights
- Level Required: 8+ years of experience in Data Engineering, Platform Engineering, Infrastructure Engineering, or related technical disciplines.
Role overview
We are building the Data Hub, a centralized data platform responsible for consolidating legacy data infrastructure, establishing enterprise-grade data foundations, and enabling advanced analytics and AI capabilities across Precision AQ. The Principal Data Engineer is a senior technical leader and hands-on contributor responsible for the design, implementation, optimization, and operation of the Data Hub’s core platform capabilities, sitting at the intersection of data engineering, platform engineering, DevOps, architecture, and data governance.
Responsibilities
- Design, build, and maintain scalable, secure, and reliable cloud-native data platform infrastructure.
- Develop infrastructure-as-code, CI/CD pipelines, deployment automation, and environment management processes.
- Partner with Corporate IT, Security, and platform vendors to ensure compliance, reliability, and operational excellence.
- Improve platform observability through monitoring, alerting, logging, and performance tracking.
- Design scalable data models supporting analytics, reporting, AI/ML, and operational use cases.
- Define and evolve data architecture standards, patterns, and best practices across the Data Hub ecosystem.
- Ensure data solutions align with governance, lineage, security, and regulatory requirements.
- Guide engineering teams in implementing maintainable and extensible data structures.
- Build and optimize data ingestion, transformation, and delivery pipelines across multiple business domains.
- Lead technical design reviews and contribute directly to implementation of complex data engineering initiatives.
- Collaborate with Product, Analytics, AI/ML, and business stakeholders to translate requirements into scalable technical solutions.
- Provide hands-on support for critical platform initiatives, migrations, and modernization programs.
- Establish and enforce software engineering, GitOps, DevOps, testing, and deployment standards.
- Drive automation across development, deployment, monitoring, and operational processes.
- Promote best practices for code quality, documentation, technical debt management, and release management.
- Conduct architecture reviews and code reviews to ensure consistency and maintainability.
- Identify and resolve performance bottlenecks across pipelines, databases, and infrastructure.
- Define and implement data quality frameworks, automated validation processes, and operational controls.
- Optimize platform cost, scalability, reliability, and processing efficiency.
- Lead root-cause analysis and remediation efforts for production incidents and operational challenges.
- Mentor Data Engineers, Analytics Engineers, and other technical contributors through coaching, code reviews, pair programming, and design guidance.
- Act as a trusted technical advisor across multiple teams and business units.
- Share knowledge, develop engineering standards, and promote continuous improvement across the Data Hub organization.
- Help elevate the technical capabilities of the broader engineering team.
- Participate in Data Hub leadership activities, including roadmap planning, prioritization discussions, technology evaluations, and executive reporting.
- Provide technical recommendations on platform investments, vendor selection, architecture direction, and engineering standards.
- Collaborate closely with Data Product Management, AI/ML teams, business stakeholders, and Corporate IT to ensure alignment between business priorities and technical execution.
Requirements
- Education: Bachelor’s degree in computer science, engineering, Information Systems, or related field (Equivalent experience considered; advanced degree preferred but not required).
- 8+ years of experience in Data Engineering, Platform Engineering, Infrastructure Engineering, or related technical disciplines.
- Demonstrated expertise designing and implementing modern cloud-based data platforms.
- Strong hands-on experience with data warehousing, orchestration, transformation, and DevOps technologies.
- Experience building and optimizing large-scale data pipelines and data models.
- Deep understanding of software engineering principles, infrastructure automation, and production operations.
- Experience operating in highly regulated, compliance-sensitive, or enterprise environments.
- Proven track record of leading technical initiatives through influence rather than direct authority.
- Advanced knowledge of cloud data platforms, modern data architecture, and platform engineering.
- Deep expertise in data modelling, query optimization, and analytical data design.
- Ability to evaluate and select appropriate technologies, frameworks, and architectural approaches.
- Expert-level SQL and strong Python skills.
- Strong understanding of CI/CD, GitOps, Infrastructure-as-Code, containerization, and deployment automation.
- Experience implementing operational monitoring, incident management, alerting, and observability solutions.
- Knowledge of security, access management, and platform governance best practices.
- Strong understanding of scalability, resilience, and performance engineering.
- Leads through credibility, expertise, and collaboration rather than formal authority, with strong mentoring and coaching capabilities.
- Comfortable facilitating technical discussions and driving consensus among diverse stakeholders with the ability to influence architecture and technology decisions across teams.
- Excellent written and verbal communication skills, able to communicate complex technical concepts to both technical and non-technical audiences.
- Effective stakeholder management across engineering, product, business, and executive teams, along with strong decision-making and prioritization skills in ambiguous environments.
Nice to have
- Advance degree.
- Experience within healthcare, life sciences, pharmaceutical, or analytics organizations.
- Experience supporting AI/ML platforms, MLOps capabilities, feature stores, or model deployment frameworks.
- Familiarity with claims, formulary, commercial, or real-world evidence datasets.
- Experience leading enterprise-scale data migrations, modernization programs, or platform consolidations.
- Exposure to global engineering teams and distributed delivery models.
Additional details
- This is not a management role; you will not have direct reports.
- As a member of the Data Hub leadership team, you will contribute to technology strategy, roadmap prioritization, architecture governance, vendor evaluation, and executive reporting.
- Technical Environment includes Data Platforms (Snowflake, AWS Redshift, S3), Transformation (dbt, Matillion), Orchestration (Airflow, Dagster), Data Governance (Snowflake Horizon), Data Quality (dbt tests, Elementary), Infrastructure & DevOps (Terraform, GitHub Actions, Azure DevOps), AI/ML (Snowpark ML, MLflow, Snowflake Feature Store, LangChain), and Languages (SQL, Python).
- Any data provided as a part of this application will be stored in accordance with the Privacy Policy (and CA Privacy Notice for CA applicants).
- Precision Medicine Group is an Equal Opportunity Employer; employment decisions are made without regard to race, color, age, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or other characteristics protected by law.
- Reasonable accommodation is available for individuals with disabilities to complete any part of the application process.
- Recruitment Fraud Warning: Precision Medicine Group will never request payment, banking details, or other sensitive financial information as part of the recruitment process.
- Originally posted on Himalayas