Principal Data Engineer

About

Join our dynamic team as a Principal Data Engineer, where you will lead the design and evolution of cutting-edge cloud-native data engineering solutions on AWS. This is an exciting opportunity to shape the future of data engineering and contribute to our enterprise-wide data strategy.

Required Skills & Qualifications

• 10 years of experience in data engineering or software engineering.
• Strong hands-on AWS experience of 4-5 years.
• Proven experience designing large-scale, production-grade data platforms.
• Expertise with core AWS data services such as Amazon S3, Glue, Redshift, EMR, Lambda, Step Functions, Kinesis/MSK.
• Strong programming skills in Python, Scala, or Java.
• Deep experience with ETL/ELT frameworks and data pipeline orchestration tools (Airflow, AWS-native equivalents, etc.).
• Solid knowledge of data modeling, distributed systems, and performance tuning.
• Experience working in CI/CD, Infrastructure as Code (Terraform, CDK, Cloud Formation).
• Strong communication skills with the ability to translate technical concepts for non-technical stakeholders.
• Prior work experience at client or in client's industry.

Preferred Skills & Qualifications

• Experience experimenting with or adopting new AWS services and driving proof-of-concepts.
• Exposure to real-time streaming architectures.
• Familiarity with data governance, security, and compliance in cloud environments.
• Experience supporting analytics, BI, or ML platforms.
• Experience with Agile Frameworks.
• AWS certifications (e.g., AWS Certified Data Analytics – Specialty, Solutions Architect).

Day-to-Day Responsibilities

• Lead the design, build, and evolution of cloud-native data engineering frameworks on AWS.
• Architect and optimize end-to-end data pipelines (batch and streaming) for performance, reliability, and scalability.
• Drive adoption and experimentation with new and emerging AWS services to improve efficiency and innovation.
• Establish engineering standards, patterns, and best practices for data ingestion, transformation, and storage.
• Collaborate with analysts and product teams to support analytics.
• Own data quality, monitoring, observability, and cost optimization strategies.
• Provide technical leadership and mentorship to mid-level data engineers.
• Participate in architectural reviews and contribute to enterprise-wide data strategy.

Company Benefits & Culture

• Comprehensive health and dental benefits.
• Flexible work arrangements and a supportive work-life balance.
• Opportunities for professional development and career advancement.