Data Engineering Lead

2 weeks ago


Kolkata, West Bengal, India Sirius Digitech Full time
Experience:

- 10-15 years of experience in data engineering and AI Labs industry
- Demonstrated experience in leading and managing data engineering teams
- Proven track record of delivering complex data engineering projects

Roles and Responsibilities:

- Lead the design, development, and implementation of scalable and efficient data engineering solutions
- Manage and mentor a team of data engineers, providing technical guidance and leadership
- Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions
- Drive innovation by evaluating and implementing new technologies and tools for data processing and analysis
- Ensure the reliability, security, and performance of data engineering systems and processes
- Develop and maintain documentation for data engineering processes, standards, and best practices
- Stay updated with the latest industry trends and best practices in data engineering and AI Labs
- Contribute to the overall data strategy and roadmap for the organization
- Education Qualification:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field

Certification required:

- Professional certifications in data engineering or related fields are an advantage
- Cloud Data Engineering certification from Azure or GCP.

Behavioural Skills:

- Strong leadership and team management skills
- Excellent communication and collaboration abilities
- Problem-solving mindset with a focus on innovation
- Adaptability and ability to work in a fast-paced and dynamic environment
- Strong decision-making and strategic thinking capabilities

Technical Skills:

- Strong data engineering skills: Proficient in data modeling, ETL processes, and developing batch/real-time data pipelines.
- Programming expertise: Skilled in Python, Scala, and SQL.
- Big data experience: Hands-on experience with Hadoop, Spark, Kafka, Databricks, and Iceberg.
- Data governance and quality: Knowledgeable in data quality, governance, and security principles.
- Cloud platforms: Deep understanding of data engineering on AWS, Azure, or GCP.
- Database management: Experience with data warehousing solutions, SQL and NoSQL databases.
- ERP/System integration: Experienced with data connections from ERP systems like SAP, Oracle, SCADA, and OSI.
- Data analytics and ML: Understanding of machine learning concepts and data analysis techniques.

Non-Negotiable Skills:

- Expertise in data modeling, ETL processes, and data pipeline development
- Strong leadership and team management skills
- Excellent communication and collaboration abilities
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