Role & responsibilities
Build and enhance ELT/ETL pipelines to ingest, transform, and curate data from multiple sources into clean, trusted datasets.
Develop and maintain data processing jobs using Spark and Python, with a focus on performance and reliability.
Implement and monitor data quality checks, reconcile issues, and partner with analysts to resolve data defects.
Translate requirements into technical tasks and deliver well-documented solutions, including runbooks and operational playbooks.
Support day-to-day operations of data pipelinesmonitoring, incident triage, root-cause analysis, and meeting SLA targets.
Develop workflows and scheduling using MWAA (Airflow) and AWS-native services.
Collaborate effectively across time zones with onsite stakeholders and the India engineering team through explicit communication and proactive status updates.

Required Skills:
Bachelors degree in computer science, Engineering, Information Systems,



or related technical field (or equivalent practical experience).
7+ years of hands-on data engineering experience building and supporting production data pipelines.
Solid SQL skills (design, tuning, troubleshooting) and experience working with relational and analytical data stores.
3+ years of coding/scripting experience with Python (Java/Scala a plus).
3+ years of experience on AWS (e.g., S3, Glue, EMR, Lambda, IAM, CloudWatch, MWAA/Airflow).
2+ years of experience with infrastructure-as-code and CI/CD practices (Terraform preferred).
2+ years of experience with Spark; streaming experience with Kafka is a plus.
Experience leveraging AI tools (e.g., GenAI assistants) to improve productivity, with an understanding of secure and responsible usage.

📌 Associate Architect Mumbai
🏢 Quantiphi Analytics Solutions
📍 Mumbai