What will you do?
own end-to-end data platforms and critical data domains across Newtap's lending and financial ecosystem
design, build, and operate scalable data pipelines powering business reporting, analytics, risk, underwriting, collections, finance, compliance, and operational decision-making
own and evolve Airflow orchestration, EMR/Spark processing, Athena query platforms, Iceberg Lakehouse tables, CDC ingestion frameworks, and Data Lake architecture
design and maintain scalable data marts, curated datasets, semantic models, and data products consumed by business and technology teams
drive improvements in platform reliability, observability, scalability, performance, cost efficiency, and data quality
lead root cause analysis and resolution of complex data quality issues, operational incidents, reconciliation gaps, and platform bottlenecks
collaborate closely with Product, Risk, Finance, Analytics, Compliance, Engineering, and Leadership teams to translate business requirements into scalable data solutions
mentor junior engineers through design reviews, code reviews, operational guidance, and engineering best practices
drive adoption of engineering standards around testing, deployment, observability, governance, security, documentation, and operational excellence
leverage AI-assisted engineering workflows to accelerate development, debugging, testing, documentation, and platform operations
contribute to the evolution of Newtap's Data Lakehouse architecture,



governance framework, metadata management, and AI-ready data foundations
drive technical decisions within their domain while balancing scalability, maintainability, reliability, and business outcomes

You should apply if you are:
4–7 years of experience in data engineering, analytics engineering, platform engineering, or backend engineering with significant production ownership
strong experience designing and operating production-grade data pipelines and distributed data processing systems
hands-on experience with Airflow, Spark, EMR, Athena, data lakes, and cloud-native data platforms
experience designing data marts, analytical datasets, and scalable data models for business consumption
strong understanding of data lakehouse architectures, CDC patterns, schema evolution, partitioning strategies, and performance optimization
experience owning production systems, troubleshooting incidents, and driving operational excellence
ability to independently solve ambiguous technical problems and drive solutions from concept to production
experience mentoring engineers and influencing engineering standards within a team
solid stakeholder management skills with the ability to align technical and business priorities
ability to leverage AI effectively for development, debugging, analysis, and productivity improvements
interest in building scalable data platforms within fintech and regulated environments

📌 Data Engineer (Vasanth Nagar)
🏢 Newtap Finance
📍 Vasanth Nagar