Viraaj HR Solutions Private Limited
Website:
viraajhrsolutions.com
Job details:
A leading India-based HR services and talent solutions firm serving clients across FinTech, BFSI, e-commerce and enterprise analytics is hiring an on-site Data Engineer to build scalable data platforms and production-grade pipelines. This role sits at the intersection of big data engineering, cloud infrastructure, and analytics enablement and is based in India (on-site).
Primary Title
Data Engineer
Role & Responsibilities
- Design, develop, and operate scalable ETL/ELT pipelines to ingest, transform, and deliver high-volume data for analytics and ML workloads.
- Implement batch and streaming data solutions using Apache Spark and Kafka to meet performance and SLA targets.
- Author and maintain orchestration workflows with Apache Airflow and ensure reliable job scheduling and alerting.
- Collaborate with data scientists and analytics teams to productionize models and deliver curated datasets into data warehouses/lakes.
- Drive data quality, schema governance, and performance tuning across pipelines and warehouses.
- Operate and optimize cloud-based data infrastructure on AWS, including provisioning, cost control, and security best practices; work on-site in India.
Skills & Qualifications Must-Have
- Python
- SQL
- Apache Spark
- Apache Airflow
- ETL pipelines
- Data Warehousing
Preferred
Qualifications: Bachelor's degree in Computer Science, Engineering, or related field (or equivalent practical experience). Prior experience building production data platforms and working on-site in India is required. Strong problem-solving, ownership mindset, and familiarity with CI/CD for data workloads are highly valued.
Benefits & Culture Highlights
- Work on high-impact analytics and ML use-cases supporting large-scale, customer-facing products.
- Learning-focused environment with exposure to modern cloud data stacks and cross-functional teams.
- Competitive compensation and opportunities for technical growth and role ownership (on-site).
Skills: pyspark,apache kafka,aws,gcp,data warehousing,sql,apache spark,etl,azure,python
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