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Manager Data Engineer @ LatentView

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 Manager Data Engineer

Job Description

Job Description:

We are looking for a highly motivated and skilled L4 Data Engineer Manager, particularly with Databricks experience, is generally responsible for leading data engineering projects, overseeing a team of data engineers, and designing data architectures on platforms like Databricks.

Responsibilities:

Leadership and Team Management:

  • Lead, mentor, and develop a team of data engineers, ensuring high performance and career growth.
  • Collaborate with stakeholders across data science, analytics, and engineering teams to deliver high-impact data solutions.
  • Oversee the data engineering project lifecycle, from requirements gathering to deployment, ensuring quality and timeliness.

Data Architecture and Strategy:

  • Develop scalable data architectures and solutions on Databricks for ETL processes, data warehousing, and big data processing.
  • Define and enforce data governance policies, best practices, and standards for data processing and management.
  • Design data flow pipelines for efficient data ingestion, storage, and processing in cloud environments (e.g., AWS, Azure, GCP).

Databricks Management and Optimization:

  • Optimize Databricks clusters for cost and performance efficiency, leveraging cluster scaling and resource management best practices.
  • Implement advanced data transformations and data models within Databricks using Spark and Delta Lake.
  • Ensure integration between Databricks and other data tools, such as data lakes, SQL databases, and BI tools.

Data Quality and Security:

  • Monitor and ensure data quality, reliability, and security within the Databricks environment.
  • Implement data validation checks, data profiling, and error-handling mechanisms.
  • Collaborate with security teams to ensure compliance with data privacy regulations and internal security standards.

Technical Development and Innovation:

  • Stay updated with the latest Databricks capabilities and cloud technology trends to introduce innovative data engineering practices.
  • Develop reusable and efficient code, libraries, and tools to automate and streamline data workflows.
  • Troubleshoot and resolve complex data pipeline issues and provide continuous improvements in performance and reliability.

 Skills:

  • Advanced experience with Databricks, PySpark and data pipeline frameworks.
  • Proficiency in Python, SQL, and/or Scala.
  • Familiarity with cloud platforms like AWS, Azure, or GCP.
  • 8+ years in data engineering, with 2+ years in a leadership or managerial role.
  • Strong experience in data architecture, data pipeline optimization, and data modeling.
  • Proven experience in managing large-scale data processing systems and ETL pipelines.
  • Familiarity with Airflow for workflow orchestration and experience with Linux administration and shell scripting.
  • Excellent communication skills to collaborate effectively with cross-functional teams.
  • Strong problem-solving abilities and attention to detail.

Job Classification

Industry: Analytics / KPO / Research
Functional Area / Department: Other
Role Category: Other
Role: Other
Employement Type: Full time

Contact Details:

Company: LatentView
Location(s): Chennai

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Keyskills:   Pyspark Data Bricks SQL

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