experience to design, build, and maintain scalable data infrastructure and pipelines. You'll work with cross-functional teams to ensure reliable data flow from various sources to analytics platforms, enabling data-driven decision making across the organization.
Key Responsibilities:
Data Pipeline Development
Design and implement robust ETL/ELT pipelines using tools like Apache Airflow, Spark, or cloud-native solutions
Build real-time and batch processing systems to handle high-volume data streams
Optimize data workflows for performance, reliability, and cost-effectiveness
Infrastructure & Architecture
Develop and maintain data warehouses and data lakes using platforms like Snowflake, Redshift, BigQuery, or Databricks
Implement data modeling best practices including dimensional modeling and schema design
Architect scalable solutions on cloud platforms (AWS, GCP, Azure)
Data Quality & Governance
Implement data quality checks, monitoring, and alerting systems
Establish data lineage tracking and metadata management
Ensure compliance with data privacy regulations and security standards
Collaboration & Support
Partner with data scientists, analysts, and business stakeholders to understand requirements
Provide technical guidance on data architecture decisions
Mentor junior engineers and contribute to team knowledge sharing
Required Qualifications:
Technical Skills
4-6 years of experience in data engineering or related field
Proficiency in Python, SQL, and at least one other programming language (Java, Scala, Go)
Strong experience with big data technologies (Spark, Kafka, Hadoop ecosystem)
Hands-on experience with cloud platforms and their data services
Knowledge of containerization (Docker, Kubernetes) and infrastructure as code
Job Types: Full-time, Permanent
Pay: ₹600,000.00 - ?800,000.00 per year
Benefits:
Health insurance
Provident Fund
Schedule:
Day shift
Monday to Friday
Work Location: In person
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