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.
- Strong 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