職種概要
Dear Candidate ,Job DescriptionBachelor’s degree in Computer Science, Engineering, Data Science, or related field (or equivalent professional experience).7+ years of experience building enterprise-scale data pipelines, platforms, and distributed data systems.Expert-level experience with Databricks and modern Lakehouse architectures.Deep expertise in Apache Spark, preferably PySpark, for large-scale distributed data processing.Strong hands-on experience with Delta Lake, Unity Catalog, Databricks Workflows, and enterprise Databricks deployments.Proficiency in Python and strong familiarity with Java.Advanced SQL skills and experience with relational and non-relational databases such as SQL Server, PostgreSQL, MySQL, and MongoDB.Strong expertise with cloud platforms, preferably AWS, including services such as S3, Redshift, IAM, and cloud-native data architectures.Experience designing and implementing modern data lakes, data warehouses, and Lakehouse solutions.Expertise with streaming platforms such as Kafka and AWS Kinesis and event-driven architectures.Strong understanding of data modeling, warehousing, schema design, and data lifecycle management.Experience with data transformation tools such as dbt and business intelligence platforms such as Looker.Experience building and exposing APIs for data consumption and integration.Strong understanding of Git, CI/CD pipelines, infrastructure automation, and software engineering best practices.Experience implementing enterprise data governance, security, and compliance controls across modern data platforms.Experience optimizing Databricks clusters, Spark workloads, storage formats, and platform costs.Strong analytical, troubleshooting, and problem-solving skills with a passion for continuous learning and innovation.Excellent communication and collaboration skills across technical and non-technical audiences.Demonstrated experience mentoring engineers, leading technical projects, and influencing architectural decisions.Please share your updated resume with below details-Total exp:Relevant exp:CTC:ECTC:Notice:Location:Pf account(yes/No):Available for f2f for the final round-bangalore/hyderabad:Available for virtual interview on 5 nov:
必要条件
- Bachelor’s degree in Computer Science, Engineering, Data Science, or related field (or equivalent professional experience).
- 7+ years of experience building enterprise-scale data pipelines, platforms, and distributed data systems.
- Expert-level experience with Databricks and modern Lakehouse architectures.
- Deep expertise in Apache Spark, preferably PySpark, for large-scale distributed data processing.
- Strong hands-on experience with Delta Lake, Unity Catalog, Databricks Workflows, and enterprise Databricks deployments.
- Proficiency in Python and strong familiarity with Java.
- Advanced SQL skills and experience with relational and non-relational databases such as SQL Server, PostgreSQL, MySQL, and MongoDB.
- Strong expertise with cloud platforms, preferably AWS, including services such as S3, Redshift, IAM, and cloud-native data architectures.
- Experience designing and implementing modern data lakes, data warehouses, and Lakehouse solutions.
- Expertise with streaming platforms such as Kafka and AWS Kinesis and event-driven architectures.
- Strong understanding of data modeling, warehousing, schema design, and data lifecycle management.
- Experience with data transformation tools such as dbt and business intelligence platforms such as Looker.
- Experience building and exposing APIs for data consumption and integration.
- Strong understanding of Git, CI/CD pipelines, infrastructure automation, and software engineering best practices.
- Experience implementing enterprise data governance, security, and compliance controls across modern data platforms.
- Experience optimizing Databricks clusters, Spark workloads, storage formats, and platform costs.
- Strong analytical, troubleshooting, and problem-solving skills with a passion for continuous learning and innovation.
- Excellent communication and collaboration skills across technical and non-technical audiences.
- Demonstrated experience mentoring engineers, leading technical projects, and influencing architectural decisions.
職務内容
- Lead a team of data engineers, providing technical direction, mentorship, and performance management.
- Design, develop, and maintain scalable data pipelines to collect, process, and store data from multiple sources.
- Architect, build, and optimize Databricks Lakehouse solutions supporting enterprise analytics, reporting, AI/ML, and data products.
- Develop large-scale distributed data processing solutions using Databricks, Apache Spark (PySpark), and Delta Lake.
- Implement and manage Medallion Architecture (Bronze, Silver, Gold) data layers to improve data quality, governance, and usability.
- Build and optimize data infrastructure to support analytics, reporting, and AI/ML workloads at scale.
- Implement event sourcing and streaming architectures using platforms such as Kafka and AWS Kinesis for real-time data processing.
- Leverage Databricks capabilities such as Auto Loader, Delta Live Tables, Databricks Workflows, Unity Catalog, and MLflow to improve platform efficiency and governance.
- Establish best practices for Databricks workspace administration, cluster management, performance tuning, monitoring, and cost optimization.
- Apply data governance, security principles, and compliance frameworks to ensure data quality and regulatory adherence.
- Collaborate with data scientists, software engineers, analytics teams, and product leaders to deliver scalable and reliable data solutions.
- Drive the adoption of modern data engineering practices, frameworks, and tooling across the organization.
- Troubleshoot and resolve complex data-related issues while maintaining data quality, availability, and integrity.
- Contribute to architectural decisions and technology roadmaps for the organization’s data platform.
- Mentor data engineers and provide technical leadership across multiple initiatives and teams.
私たちが提供するもの
Exciting Projects: We focus on industries like High-Tech, communication, media, healthcare, retail and telecom. Our customer list is full of fantastic global brands and leaders who love what we build for them.
Collaborative Environment: You Can expand your skills by collaborating with a diverse team of highly talented people in an open, laidback environment — or even abroad in one of our global centers or client facilities!
Work-Life Balance: GlobalLogic prioritizes work-life balance, which is why we offer flexible work schedules, opportunities to work from home, and paid time off and holidays.
Professional Development: Our dedicated Learning & Development team regularly organizes Communication skills training(GL Vantage, Toast Master),Stress Management program, professional certifications, and technical and soft skill trainings.
Excellent Benefits: We provide our employees with competitive salaries, family medical insurance, Group Term Life Insurance, Group Personal Accident Insurance , NPS(National Pension Scheme ), Periodic health awareness program, extended maternity leave, annual performance bonuses, and referral bonuses.
Fun Perks: We want you to love where you work, which is why we host sports events, cultural activities, offer food on subsidies rates, Corporate parties. Our vibrant offices also include dedicated GL Zones, rooftop decks and GL Club where you can drink coffee or tea with your colleagues over a game of table and offer discounts for popular stores and restaurants!
GlobalLogicについて
GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world’s largest and most forward-thinking companies. Since 2000, we’ve been at the forefront of the digital revolution – helping create some of the most innovative and widely used digital products and experiences. Today we continue to collaborate with clients in transforming businesses and redefining industries through intelligent products, platforms, and services.
