Data Engineer

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. We are passionate about our customers and obsessed with problem-solving to make products smarter, customer experiences frictionless, processes autonomous and businesses safer by detecting risks, threats and anomalies. Together with partners and customers, we embark on a data and AI led transformation journey that delivers impactful and measurable results.

JOB ROLE - Associate Technical Architect

Role Overview:

As an Associate Technical Architect - Data, you will lead the end-to-end design, architecture, and implementation of enterprise-scale AWS data platforms and Lakehouse solutions. You will provide technical leadership across the entire project lifecycle - from solution architecture and technology selection to implementation, optimization, deployment, and production support. The role requires deep hands-on expertise in modern AWS data engineering technologies, strong architectural skills, and the ability to mentor engineering teams while collaborating with business and technical stakeholders to deliver scalable, secure, and high-performance data solutions.

Must have Skills:

• 8+ years of experience designing and delivering enterprise-scale Data Lake, Lakehouse, or Data Warehouse solutions on AWS.
• Proven experience leading end-to-end implementation of cloud-native data platforms, including architecture, design, development, deployment, and production support.
• Strong hands-on expertise in SQL (analytical queries, window functions, stored procedures), Spark/PySpark, and Python.
• Strong hands-on experience designing and implementing Lakehouse architectures using Apache Iceberg.
• Strong knowledge of AWS services including EMR, S3, Athena, Glue Catalog, Aurora PostgreSQL, Lambda, CloudWatch, SQS, SNS, EventBridge, IAM, and related AWS data services.
• Experience designing and implementing scalable batch and streaming data pipelines using AWS native services.
• Strong expertise in Spark/PySpark performance tuning and optimization.
• Hands-on experience optimizing Apache Iceberg and Aurora PostgreSQL for performance, scalability, and cost efficiency.
• Strong understanding of data modeling, distributed data processing, partitioning strategies, file formats, and Lakehouse/Data Lake architectures.
• Strong understanding of AWS architecture principles, including security, networking, disaster recovery, scalability, resiliency, and cost optimization.
• Experience designing orchestration workflows using Apache Airflow or AWS Step Functions.
• Ability to define cloud data platform architectures, evaluate technology choices, and articulate architectural trade-offs and best practices.
• Experience leading globally distributed engineering teams, mentoring developers, conducting architecture/code reviews, and driving engineering best practices.
• Excellent communication, stakeholder management, problem-solving, and technical leadership skills with the ability to translate business requirements into scalable technical solutions.
• AWS Solution Architect Associate/Professional or AWS Data Engineer Associate certification is preferred.

Good to have skills:

• Experience with ClickHouse, including performance tuning and query optimization.
• Experience with Infrastructure as Code using Terraform or CloudFormation.
• Experience implementing CI/CD pipelines for data engineering workloads.
• Exposure to Kafka, Hive, HDFS, or other Big Data technologies.
• Hands-on experience using GenAI-assisted development tools such as Kiro, GitHub Copilot, Cursor, or similar AI coding assistants to improve engineering productivity.
• Experience integrating with data governance and metadata management tools such as Collibra.
• Experience integrating with data virtualization platforms such as Denodo.
• Telecom/Mobile Network domain knowledge is preferred but not mandatory.

For more details visit our website or our LinkedIn Page