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Job Description & How to Apply Below
We at Verdantas, seeking a Data Engineer Lead in Pune to architect and implement scalable, secure AI/ML data solutions aligned with business objectives. The role involves designing robust batch and real-time data architectures, leading ETL/ELT pipeline development, managing data lakes and warehouses, ensuring data quality and governance, mentoring data engineers, collaborating with stakeholders, and deploying cloud-based data infrastructure with CI/CD and cost optimization.
Candidates should have 8+ years in data engineering with leadership experience, strong skills in SQL, Python, distributed processing frameworks, and cloud-native data services, with preferred certifications including Google Professional Data Engineer, Azure Data Engineer Associate, and AWS Certified Data Analytics Specialty. The position requires in-office work in Pune, Maharashtra, India.
Key Responsibilities
Architecture & Strategy
Design and implement robust data architectures (batch and real-time) using modern data platforms.
Define data engineering standards, best practices, and governance policies.
Evaluate and recommend tools and technologies for data ingestion, storage, processing, and orchestration.
Development & Operations
Lead the development of ETL/ELT pipelines using tools like Apache Spark, Airflow, dbt, or Azure Data Factory.
Build and manage data lakes, data warehouses, and data marts.
Ensure data quality, lineage, and observability across pipelines.
Team Leadership
Mentor and guide data engineers, fostering a culture of technical excellence and continuous improvement.
Collaborate with data scientists, analysts, and business stakeholders to understand data needs and deliver solutions.
Manage project timelines, resource allocation, and delivery milestones.
Cloud & Dev Ops Integration
Deploy and manage data infrastructure on cloud platforms (AWS, Azure, GCP).
Implement CI/CD pipelines for data workflows and infrastructure as code (IaC).
Optimize performance and cost of data systems.
Skills & Qualifications
Bachelor’s or master’s in computer science, Data Engineering, or related field.
8+ years of experience in data engineering, with 2+ years in a leadership role.
Strong expertise in SQL, Python, and distributed data processing frameworks (Spark, Flink).
Experience with cloud-native data services (e.g., AWS Glue, Azure Synapse, Big Query).
Familiarity with data modeling, data governance, and metadata management.
Excellent problem-solving, communication, and stakeholder management skills.
Preferred
Certifications:
Google Professional Data Engineer
Microsoft Certified:
Azure Data Engineer Associate
AWS Certified Data Analytics – Specialty
Location and Work Set-up
· Pune, Maharashtra, India
· Work Mode:
In Office
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