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Data Engineer-Data Platforms-AWS

IBM · Posted Oct 24

Hybrid cloud, artificial intelligence, enterprise software, quantum computing, and IT consulting services

Multiple CitiesFull-timeHybridSenior Level4+ years₹15.0L–₹28.0L yearly36 applicants
Information TechnologyCloud ComputingArtificial IntelligenceQuantum ComputingEnterprise SoftwareIT ConsultingPublic Company
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About the role

IBM Consulting works with clients worldwide to shape hybrid cloud and AI journeys, supported by IBM technology and Red Hat. The role focuses on AWS data platforms, including serverless and containerized workloads, Apache Spark processing, AWS Glue/Athena analytics, and infrastructure as code. The Data Engineer will design, build, and support scalable, secure, high-performance data solutions with architects, application teams, and business stakeholders.

What you will do

  • Design, develop, and maintain data pipelines and data platforms on AWS
  • Build and operate serverless and containerized workloads using AWS Lambda, EC2, and EKS
  • Develop batch and large-scale data processing solutions using Apache Spark
  • Implement data ingestion, transformation, and analytics using AWS Glue and Athena
  • Write complex and high-performance SQL queries for analytics, reporting, and data validation
  • Manage and optimize data storage solutions using AWS S3 and RDS
  • Design and manage AWS infrastructure using Infrastructure as Code (IaC) with CloudFormation
  • Apply AWS security best practices across IAM, VPC networking, data encryption, and access controls
  • Develop clean, scalable, and maintainable code using Python and/or Scala
  • Monitor, troubleshoot, and optimize performance, cost, and reliability of data workloads
  • Collaborate with cross-functional teams to support analytics, reporting, and regulatory use cases

Skills used in this role

AWSAmazon S3AWS LambdaAmazon EC2Amazon EKSApache SparkAWS GlueAmazon AthenaSQLAmazon RDSAWS CloudFormationAWS IAMAmazon VPCPythonScalaETL/ELTData ModelingDistributed SystemsdbtSnowflakeDatabricksAmazon EMRAmazon KinesisApache KafkaCommunication

What the employer is looking for

  • Strong hands-on experience with AWS services, including o S3, Lambda, EC2, EKS o AWS Glue, Athena o RDS o VPC, IAM o CloudFormation
  • Strong SQL skills, including o Writing complex queries, joins, aggregations, and user defined functions o Performance tuning and query optimization
  • Good knowledge of AWS Security, including IAM policies, VPC security, encryption, and least-privilege access
  • Hands-on programming experience with Python and/or Scala
  • Strong experience with Apache Spark for large-scale data processing
  • Good communication skills to explain technical concepts to non-technical stakeholders
  • Solid understanding of data engineering concepts such as ETL/ELT, data modeling, and distributed systems

Preferred qualifications

  • Experience with DBT for data transformations
  • Hands-on exposure to Snowflake
  • Experience working with Databricks
  • Familiarity with modern data lake / Lakehouse architectures
  • Experience working in enterprise or regulated environments
  • Strong analytical and problem-solving skills
  • Ability to work independently and in distributed teams
  • Exposure to AWS Toolset: Experience working with AWS services such as AWS EMR, AWS Glue, Glue Catalog, and Kinesis to design, build, and operate batch and real-time data pipelines.
  • Data Pipeline Development: Exposure to developing batch and real-time data pipelines for Data Warehouse and Datalake, utilizing AWS Kinesis and Managed Streaming for Apache Kafka.
  • Data Layer Creation: Experience working with AWS RedShift, Aurora, and DynamoDB to create data layers and migrate data using AWS DMS.
  • Open Source Technologies: Exposure to utilizing open source technologies like Apache Airflow and dbt, Spark / Python or Spark / Scala on AWS Platform to support data engineering solutions.
  • Data Service Management: Experience scheduling and managing data services on the AWS Platform, ensuring efficient operation of data engineering solutions.
  • Proficiency with AWS Databrew: Experience working with AWS Glue Databrew to support data engineering solutions, including data preparation and data quality tasks.
  • Knowledge of Lambda Functions: Exposure to using Lambda functions with Python to support data engineering solutions, including data processing and data transformation tasks.
  • Familiarity with RedShift Spectrum: Experience working with RedShift Spectrum to support data engineering solutions, including data warehousing and data analytics tasks.

Benefits and support

  • Compensation and benefits are detailed in the job posting

About IBM

International Business Machines Corporation (IBM) is a global technology and consulting company that provides hybrid cloud, artificial intelligence, and enterprise infrastructure solutions. Operating in over 175 countries, IBM helps businesses across industries modernize operations, secure data, and drive digital transformation through platforms like watsonx and Red Hat OpenShift. Founded over a century ago, the company remains a pioneer in high-performance computing, enterprise automation, and quantum technology.

Industry
Information Technology
Company size
260,000+ employees
Founded
June 16, 1911
Location
Armonk, New York, USA
Funding stage
Public Company

Funding

Public Company · $3.5B raised

Institutional Public ShareholdersVanguard GroupBlackRock
  • ·Post Ipo Debt$150M

Leadership

AK
Arvind Krishna

Chairman, President and Chief Executive Officer

JJ
James J. Kavanaugh

Senior Vice President and Chief Financial Officer

RT
Rob Thomas

Senior Vice President, Software and Chief Commercial Officer

MA
Mohamad Ali

Senior Vice President, IBM Consulting

JH
Jonathan H. Adashek

Senior Vice President, Marketing and Communications

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