While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!
JOB ROLE - Senior Data Engineer
As a Senior Data Engineer, you will be responsible for designing, developing, and optimizing scalable cloud-native data platforms on AWS. You will build high-performance batch and analytical data pipelines using Spark/PySpark, Apache Iceberg, and AWS services, while ensuring reliability, performance, and operational excellence. The role requires strong hands-on expertise in data engineering, SQL optimization, distributed data processing, and cloud-native architectures.
Must have skills:
3+ years of hands-on experience building large-scale AWS data engineering solutions.
Strong hands-on expertise in SQL (analytical queries, window functions, stored procedures), Spark/PySpark, and Python.
Hands-on experience designing and implementing Lakehouse solutions using Apache Iceberg.
Strong knowledge of AWS services including EMR, S3, Athena, Glue Catalog, Aurora PostgreSQL, Lambda, CloudWatch, SQS, SNS, EventBridge, and IAM.
Experience building scalable batch and streaming data pipelines on AWS.
Strong experience in Spark/PySpark performance tuning and optimization.
Hands-on experience optimizing Apache Iceberg and Aurora PostgreSQL for performance and scalability.
Strong understanding of data modeling, partitioning, file formats, and Lakehouse/Data Lake architectures.
Experience implementing monitoring, logging, alerting, and observability for production data pipelines.
Strong knowledge of data quality, troubleshooting, debugging, and production support.
Experience with CI/CD, Git, and data engineering best practices.
Strong communication, problem-solving, and stakeholder management skills.
AWS Data Engineer Associate or equivalent AWS Certification is preferred.
Good to have skills :
Experience with Apache Airflow or AWS Step Functions.
Experience with Terraform or Infrastructure as Code.
Exposure to Kafka, Hive, HDFS or other Big Data technologies.
Hands-on experience using GenAI-assisted development tools such as Kiro, Copilot,Cursor, or similar AI coding assistants to improve engineering productivity.
Experience with ClickHouse Database
Telecom/Mobile Network domain knowledge is preferred.
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
Skills Required
- 3+ years of hands-on experience building large-scale AWS data engineering solutions
- Strong expertise in SQL (analytical queries, window functions, stored procedures)
- Strong hands-on experience with Spark/PySpark and Python
- Hands-on experience designing and implementing Lakehouse solutions using Apache Iceberg
- Strong knowledge and hands-on experience with AWS services: EMR, S3, Athena, Glue Catalog, Aurora PostgreSQL, Lambda, CloudWatch, SQS, SNS, EventBridge, IAM
- Experience building scalable batch and streaming data pipelines on AWS
- Experience in Spark/PySpark performance tuning and optimization
- Hands-on experience optimizing Apache Iceberg and Aurora PostgreSQL for performance and scalability
- Strong understanding of data modeling, partitioning, file formats, and Lakehouse/Data Lake architectures
- Experience implementing monitoring, logging, alerting, and observability for production data pipelines
- Strong knowledge of data quality, troubleshooting, debugging, and production support
- Experience with CI/CD and Git and adherence to data engineering best practices
- Strong communication, problem-solving, and stakeholder management skills
- AWS Data Engineer Associate or equivalent AWS Certification
- Experience with Apache Airflow or AWS Step Functions
- Experience with Terraform or Infrastructure as Code
- Exposure to Kafka, Hive, HDFS or other Big Data technologies
- Hands-on experience using GenAI-assisted development tools (Kiro, Copilot, Cursor, or similar)
- Experience with ClickHouse database
- Telecom/Mobile Network domain knowledge
Quantiphi Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Quantiphi and has not been reviewed or approved by Quantiphi.
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Wellbeing & Lifestyle Benefits — Wellbeing initiatives such as monthly meeting-free AMA-Zen Days, health check-ups, and wellness counseling are designed to reduce burnout and support day-to-day balance. Broader wellness programs reinforce both physical and mental health.
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Flexible Benefits — Remote/hybrid options with flexible working hours provide meaningful autonomy over where and when work gets done. Flexible leave constructs, including sabbaticals and special day leaves, add practical adaptability to the package.
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Parental & Family Support — Paid parental leave in the U.S., alongside maternity and childcare support, signals solid backing for families. These family-oriented policies integrate with a wider health and wellness focus.
Quantiphi Insights
What We Do
Quantiphi is an award-winning AI-first digital engineering company driven by the desire to solve transformational problems at the heart of business. Quantiphi solves the toughest and complex business problems by combining deep industry experience, disciplined cloud, and data-engineering practices, and cutting-edge artificial intelligence research to achieve quantifiable business impact at unprecedented speed.
