Data Engineering Team Lead

6 days ago

Coimbatore, Tamil Nadu, India beBeeSolution Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Job Title:

.NET Technical Solution Architect



Location:

Bangalore, Coimbatore.



Experience Needed:

Minimum 8+ Years of experience in data engineering and analytics, with at least 3–5 years in a leadership role.



Job Type:

Full-time (Work from office 5 days a week)



Responsibilities:

As the primary point of contact for customers, you will ensure successful delivery of data and analytics solutions. You will also translate complex customer requirements into scalable, high-impact data solutions. Maintaining a strong focus on stakeholder engagement and satisfaction, ensuring delivery meets or exceeds expectations.



Key Responsibilities Include:
  1. Serve as the primary point of contact for customers, ensuring successful delivery of data and analytics solutions.
  2. Translate complex customer requirements into scalable, high-impact data solutions.
  3. Maintain a strong focus on stakeholder engagement and satisfaction, ensuring delivery meets or exceeds expectations.


Technical Skills Required:
  1. Architect and implement scalable, cloud-agnostic data solutions using technologies such as Big Data, streaming Platforms Databricks, Snowflake, Redshift, python, pyspark, Kafka, SQL Server, PostgreSQL on any Cloud (AWS/Azure/GCP).
  2. Stay ahead of technology trends in data engineering, cloud computing, and big data platforms to ensure competitive offerings.
  3. Evaluate and adopt emerging tools and frameworks that enhance productivity, performance, and innovation.


Collaboration and Leadership:
  1. Act as a bridge between technical and non-technical stakeholders, translating business needs into technical execution.
  2. Promote knowledge sharing and alignment across functional and geographical team boundaries.
  3. Lead, mentor, and develop a high-performing global team of 20+ data professionals across onshore and offshore locations.


Process Improvement and Reporting:
  1. Define and continuously refine best practices in Technology frameworks and operational processes.
  2. Drive improvements in data quality, performance, and governance across the data lifecycle.
  3. Track team utilization and proactively forecast upcoming bench time, ensuring maximum billing efficiency and planning for resource allocation.

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