Azure Data Lead

Job Description

Job ID: Azu-ETP-Pun-1209 Location: Pune,Other Data Engineer Lead Company Overview Bridgenext is a digital consulting services leader that helps clients innovate with intention and realize their digital aspirations by creating digital products, experiences, and solutions around what real people need. Our global consulting and delivery teams facilitate highly strategic digital initiatives through digital product engineering, automation, data engineering, and infrastructure modernization services, while elevating brands through digital experience, creative content, and customer data analytics services. Don?t just work, thrive. At Bridgenext, you have an opportunity to make a real difference ? driving tangible business value for clients, while simultaneously propelling your own career growth. Our flexible and inclusive work culture provides you with the autonomy, resources, and opportunities to succeed The Role: As a Lead Data Engineer specializing in Databricks, you will be a key player in designing, developing, and optimizing our next-generation data platform. You will lead a team of data engineers, providing technical guidance, mentorship, and ensuring the scalable, and high-performance data solutions. Key Responsibilities Technical Leadership: Lead the design, development, and implementation of scalable and reliable data pipelines using Databricks, Spark, and other relevant technologies. Define and enforce data engineering best practices, coding standards, and architectural patterns. Provide technical guidance and mentorship to junior and mid-level data engineers. Conduct code reviews and ensure the quality, performance, and maintainability of data solutions. Databricks Expertise: Architect and implement data solutions on the Databricks platform, including Databricks Lakehouse, Delta Lake, and Unity Catalog. Optimize Spark workloads for performance and cost efficiency on Databricks. Develop and manage Databricks notebooks, jobs, and workflows. Proficiently use Databricks features such as Delta Live Tables (DLT), Photon, and SQL Analytics. Pipeline Development & Operations: Develop, test, and deploy robust ETL/ELT pipelines for data ingestion, transformation, and loading from various sources (e.g., relational databases, APIs, streaming data). Implement monitoring, alerting, and logging for data pipelines to ensure operational excellence. Troubleshoot and resolve complex data-related issues. Collaboration & Communication: Work closely with cross-functional teams including product managers, data scientists, and software engineers. Communicate complex technical concepts clearly to both technical and non-technical stakeholders. Stay updated with industry trends and emerging technologies in data engineering and Databricks Primary Skills Extensive hands-on experience with Databricks platform, including Databricks Workspace, Spark on Databricks, Delta Lake, and Unity Catalog. Strong proficiency in optimizing Spark jobs and understanding Spark architecture. Experience with Databricks features like Delta Live Tables (DLT), Photon, and Databricks SQL Analytics. Deep understanding of data warehousing concepts, dimensional modeling, and data lake architectures.