Kolkata, West Bengal, India
Information Technology
Full-Time
AEON Software
Overview
Job Overview
Seeking an experienced Data Engineer who had 4 to 5 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 :
Technical Skills :
Seeking an experienced Data Engineer who had 4 to 5 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.
- 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).
- Implement data quality checks, monitoring, and alerting systems.
- Establish data lineage tracking and metadata management.
- Ensure compliance with data privacy regulations and security standards.
- 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.
Technical Skills :
- 4-5 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.
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