Lead Data Engineer

Stryker India Private Limited; Gurugram District; Hybrid; INR 3,000,000 - 6,000,000; Full time

Job summary

Stryker India Private Limited is seeking a Lead Engineer for EDT Data & Analytics - Data Engineering. The role focuses on designing, building, and optimizing large-scale data pipelines and cloud data platforms to support enterprise analytics and reporting.

You will mentor engineers and collaborate with architecture and product teams to uphold high engineering standards. Ideal candidates have 6–8 years in data engineering, strong SQL/Python/Scala/Java skills, and hands-on experience with

Qualifications

• 6–8 years of data engineering or related roles.

Responsibilities

• Lead ETL/ELT pipelines architecture and optimization.
• Develop cloud-based data platforms for enterprise analytics.
• Establish data quality, governance, security frameworks.
• Mentor engineering teams and collaborate with stakeholders.
• Design scalable batch and streaming data architectures.

Skills

SQL

Python

Scala

Java

Data architecture

Mentoring

Education

Bachelor’s degree in Computer Science/Engineering/Info Systems

Tools

Snowflake

Databricks

AWS Redshift

Azure Synapse

Apache Airflow

Azure Data Factory

dbt

Kafka

Kinesis

Event Hubs

Docker

Kubernetes

Job description

Lead Engineer, EDT Data & Analytics - Data Engineering (Work Flexibility: Hybrid)

The Lead Data Engineer leads the design, development, and optimization of complex, high-scale data pipelines and platform solutions across the Data and Analytics organization. This role provides technical leadership, mentors junior engineers, and partners with Data Architecture, Analytics, and Platform teams to define engineering standards, drive best practices, and deliver reliable, well-governed data solutions that support enterprise analytics and reporting needs.

What you will do:

Lead the architecture and optimization of scalable ETL/ELT pipelines, data models, and cloud-based data platforms to power enterprise analytics. Drive engineering excellence through automation, orchestration, CI/CD, performance tuning, and adoption of best practices across the data landscape. Establish robust data quality, governance, security, and monitoring frameworks to ensure reliable and trusted data solutions. Mentor engineering teams and collaborate with business, product, and architecture stakeholders to deliver high-impact, scalable data products. Expert in designing scalable batch and streaming data architectures, delivering high-performance and cost-efficient data solutions. Advanced proficiency in SQL, Python, Scala, and distributed processing frameworks with deep expertise in cloud data platforms. Strong technical leader who mentors engineers, drives architectural decisions, and translates complex concepts for diverse stakeholders. Proven ability to manage multiple priorities, mitigate risks, reduce technical debt, and deliver strategic outcomes with minimal oversight.

What you will need :

Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related discipline required with 6-8 years of experience in data engineering, data platform development, or related technical roles. Advanced expertise in SQL, Python/Scala/Java, and cloud-based data engineering, with a proven track record of building scalable, production-grade data pipelines and optimizing modern data platforms. Strong technical leader with deep knowledge of data architecture and modeling, recognized for mentoring teams, driving design excellence , and managing stakeholders to deliver high-impact business outcomes. Deep experience with cloud data platforms such as Snowflake, Databricks, AWS Redshift, or Azure Synapse. Advanced experience with orchestration tools such as Apache Airflow, Azure Data Factory, or dbt at enterprise scale, and streaming/event-driven architectures such as Kafka, Kinesis, or Event Hubs. Strong background in CI/CD, infrastructure-as-code, and containerization (Docker/Kubernetes) for data platforms. Advanced knowledge of data modeling techniques (dimensional modeling, star schema, data vault) and metadata/data governance practices, knowledge of Data Lake, Lakehouse and Unity Catalogue Concepts, use of Tool’s AI features to bring efficiency in Coding and bug fixing Advanced cloud platform certification (AWS, Azure, or GCP Data Engineer/Architect track) preferred./ Snowflake, Databricks, or equivalent advanced data platform certification preferred.

Travel Percentage: None Experience Level Senior Level