Seeking an experienced Data Engineer who had 4 to 6 years 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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