Lead Engineer, EDT Data & Analytics - Data Engineering

Stryker; Gurugram District; Hybrid; INR 4,000,000 - 7,000,000; Full time

Job summary

Stryker in India seeks a Lead Data Engineer to design and optimize high-scale data pipelines and platform solutions across the Data and Analytics function. You will provide technical leadership, mentor engineers, and partner with Data Architecture, Analytics, and Platform teams to codify standards and deliver reliable data products.

This role emphasizes cloud-based platforms, batch and streaming architectures, and governance across data lake environments.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related discipline with 6-8 years of experience in data engineering or related technical roles.
• Advanced expertise in SQL, Python/Scala/Java and cloud-based data engineering, building scalable, production-grade data pipelines and optimizing data platforms.
• Deep knowledge of data architecture and modeling, mentoring teams, driving design excellence, and stakeholder management to deliver high-impact outcomes.
• Experience with cloud data platforms such as Snowflake, Databricks, AWS Redshift, or Azure Synapse.
• Experience with orchestration tools such as Airflow, Azure Data Factory or dbt at enterprise scale, and streaming architectures like Kafka/Kinesis.
• Strong CI/CD, infrastructure-as-code, and containerization (Docker/Kubernetes) for data platforms.
• Knowledge of data modeling techniques and metadata governance; familiarity with Data Lake, Lakehouse concepts, and related tooling.

Responsibilities

• Lead the architecture and optimization of scalable ETL/ELT pipelines and cloud-based data platforms for enterprise analytics.
• Drive engineering excellence through automation, orchestration, CI/CD, performance tuning, and best practices adoption.
• Establish data quality, governance, security, and monitoring frameworks for reliable data solutions.
• Mentor engineering teams and collaborate with business, product, and architecture stakeholders to deliver high-impact data products.
• Design scalable batch and streaming data architectures to deliver high-performance and cost-efficient data solutions.
• Translate complex concepts for diverse stakeholders while driving architectural decisions and balancing multiple priorities.

Skills

SQL

Python

Scala

Java

Data modeling

Data architecture

Mentoring

Leadership

CI/CD

Cloud data platforms

Education

Bachelor's degree in Computer Science or related

Tools

Airflow

dbt

Snowflake

Databricks

AWS Redshift

Azure Synapse

Kubernetes

Docker

Kafka

Job description

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, andstreaming/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 bringefficiency 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.