Description:
- Data engineer with 4 to 6 years of hands on experience working on Big Data Platforms
- Experience building and optimizing Big data data pipelines and data sets ranging from Data ingestion to Processing to Data Visualization.
- Good Experience in writing and optimizing Spark Jobs, Spark SQL etc. Should have worked on both batch and steaming data processing
- Good experience in any one programming language -Scala/Python , Python preferred.
- Experience in writing and optimizing complex Hive and SQL queries to process huge data. good with UDFs, tables, joins,Views etc
- Experience in using Kafka or any other message brokers
- Configuring, monitoring and scheduling of jobs using Oozie and/or Airflow
- Processing streaming data directly from Kafka using Spark jobs, expereince in Spark- streaming is must
- Should be able to handling different file formats (ORC, AVRO and Parquet) and unstructured data
- Should have experience with any one No SQL databases like Amazon S3 etc
- Should have worked on any of the Data warehouse tools like AWS Redshift or Snowflake or BigQuery etc
- Work expereince on any one cloud AWS or GCP or Azure
Requirements:
- Data engineer with 4 to 6 years of hands on experience working on Big Data Platforms
- Experience building and optimizing Big data data pipelines and data sets ranging from Data ingestion to Processing to Data Visualization.
- Good Experience in writing and optimizing Spark Jobs, Spark SQL etc. Should have worked on both batch and steaming data processing
- Good experience in any one programming language -Scala/Python , Python preferred.
- Experience in writing and optimizing complex Hive and SQL queries to process huge data. good with UDFs, tables, joins,Views etc
- Experience in using Kafka or any other message brokers
- Configuring, monitoring and scheduling of jobs using Oozie and/or Airflow
- Processing streaming data directly from Kafka using Spark jobs, expereince in Spark- streaming is must
- Should be able to handling different file formats (ORC, AVRO and Parquet) and unstructured data
- Should have experience with any one No SQL databases like Amazon S3 etc
- Should have worked on any of the Data warehouse tools like AWS Redshift or Snowflake or BigQuery etc
- Work expereince on any one cloud AWS or GCP or Azure
Good to have skills:
- Experience in AWS cloud services like EMR, S3, Redshift, EKS/ECS etc
- Experience in GCP cloud services like Dataproc, Google storage etc
- Experience in working with huge Big data clusters with millions of records
- Experience in working with ELK stack, specially Elasticsearch
- Experience in Hadoop MapReduce, Apache Flink, Kubernetes etc
Preferences:
- Data engineer with 4 to 6 years of hands on experience working on Big Data Platforms
- Experience building and optimizing Big data data pipelines and data sets ranging from Data ingestion to Processing to Data Visualization.
- Good Experience in writing and optimizing Spark Jobs, Spark SQL etc. Should have worked on both batch and steaming data processing
- Good experience in any one programming language -Scala/Python , Python preferred.
- Experience in writing and optimizing complex Hive and SQL queries to process huge data. good with UDFs, tables, joins,Views etc
- Experience in using Kafka or any other message brokers
- Configuring, monitoring and scheduling of jobs using Oozie and/or Airflow
- Processing streaming data directly from Kafka using Spark jobs, expereince in Spark- streaming is must
- Should be able to handling different file formats (ORC, AVRO and Parquet) and unstructured data
- Should have experience with any one No SQL databases like Amazon S3 etc
- Should have worked on any of the Data warehouse tools like AWS Redshift or Snowflake or BigQuery etc
- Work expereince on any one cloud AWS or GCP or Azure
Job Responsibilities:
- Data engineer with 4 to 6 years of hands on experience working on Big Data Platforms
- Experience building and optimizing Big data data pipelines and data sets ranging from Data ingestion to Processing to Data Visualization.
- Good Experience in writing and optimizing Spark Jobs, Spark SQL etc. Should have worked on both batch and steaming data processing
- Good experience in any one programming language -Scala/Python , Python preferred.
- Experience in writing and optimizing complex Hive and SQL queries to process huge data. good with UDFs, tables, joins,Views etc
- Experience in using Kafka or any other message brokers
- Configuring, monitoring and scheduling of jobs using Oozie and/or Airflow
- Processing streaming data directly from Kafka using Spark jobs, expereince in Spark- streaming is must
- Should be able to handling different file formats (ORC, AVRO and Parquet) and unstructured data
- Should have experience with any one No SQL databases like Amazon S3 etc
- Should have worked on any of the Data warehouse tools like AWS Redshift or Snowflake or BigQuery etc
- Work expereince on any one cloud AWS or GCP or Azure
Good to have skills:
- Experience in AWS cloud services like EMR, S3, Redshift, EKS/ECS etc
- Experience in GCP cloud services like Dataproc, Google storage etc
- Experience in working with huge Big data clusters with millions of records
- Experience in working with ELK stack, specially Elasticsearch
- Experience in Hadoop MapReduce, Apache Flink, Kubernetes etc
What We Offer
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!
About GlobalLogic GlobalLogic is a leader in digital engineering. We help brands across the globe design and build innovative products, platforms, and digital experiences for the modern world. By integrating experience design, complex engineering, and data expertise—we help our clients imagine what’s possible, and accelerate their transition into tomorrow’s digital businesses. Headquartered in Silicon Valley, GlobalLogic operates design studios and engineering centers around the world, extending our deep expertise to customers in the automotive, communications, financial services, healthcare and life sciences, manufacturing, media and entertainment, semiconductor, and technology industries. GlobalLogic is a Hitachi Group Company operating under Hitachi, Ltd. (TSE: 6501) which contributes to a sustainable society with a higher quality of life by driving innovation through data and technology as the Social Innovation Business.
