About The Opportunity
A fast-scaling tech talent solutions firm operating in the AI/ML and enterprise data infrastructure space, we partner with global enterprises to design, build, and deploy scalable data ecosystems—from cloud data warehouses to real-time streaming pipelines. Our engineers work at the intersection of data architecture, automation, and business intelligence to turn raw data into actionable insights for Fortune 500 clients.
Role & Responsibilities
- Design, build, and maintain scalable ETL/ELT pipelines using Python, SQL, and cloud-native tools for ingestion, transformation, and consumption.
- Architect and optimize data models in cloud data warehouses (Snowflake, BigQuery, Redshift) aligned with business KPIs and analytics use cases.
- Collaborate with Data Scientists and Analysts to ensure clean, structured, and well-documented datasets for ML training and reporting.
- Automate data quality checks, lineage tracking, and monitoring alerts to ensure pipeline reliability and SLA adherence.
- Implement data governance and metadata standards using tools like Apache Atlas or Collibra to ensure compliance and observability.
- Support cloud migration initiatives by refactoring legacy ETL jobs into modular, containerized, and serverless architectures.
Skills & Qualifications
- Must-Have
- Python
- SQL
- Apache Airflow
- Spark
- Snowflake
- BigQuery
- AWS or Azure cloud platforms
- Git
- Preferred
- dbt
- Star schema modeling
- Real-time streaming (Kafka, Flink)
Benefits & Culture Highlights
- Work with global clients and cross-functional teams in a high-impact, agile environment.
- Opportunity to upskill in GenAI/LLM data pipelines and modern data mesh architectures.
- Flexible work hours with onsite collaboration in tier-1 Indian tech hubs (Hyderabad, Bangalore, Pune).
Skills: design,pipelines,ml,sql,data,etl,python
