Cloud Data Engineering Manager

1 month ago

Delhi, Delhi, India Retail Kloud9 Technologies India Private Limited Full time
Job Title : Data Engineering Manager (Remote)

Location : Remote

Position Type : Full-time / Consultant

Experience : 10-12 yrs

Job Description :

We are seeking an experienced Data Engineering Manager who is hands-on in managing and delivering complex cloud-based data engineering projects, including data lake implementations.

The ideal candidate will lead engagements from pre-sales through to delivery, ensuring high-quality outcomes in terms of data architecture, storage, transformation, and analytics.

This role requires a strong technical background in modern cloud technologies, data governance, and quality :

  • Lead the design and implementation of large-scale data engineering projects, including data lakes and data pipelines on cloud platforms like AWS, Azure, or GCP.
  • Drive the pre-sales process by engaging with clients, understanding requirements, and developing technical proposals and proof of concepts (PoCs).
  • Architect scalable and secure data storage solutions using technologies like Amazon S3, Azure Data Lake Storage, and Google Cloud Storage.
  • Oversee the development of ETL/ELT pipelines using tools such as AWS Glue, Apache Spark, Databricks, or Azure Data Factory.
  • Ensure efficient data transformation and quality assurance processes by leveraging tools like AWS Lambda, Google Cloud Functions, or Azure Functions for serverless computing.
  • Implement data governance frameworks to ensure data quality and compliance using services like AWS Lake Formation, Azure Purview, or Google Data Catalog.
  • Collaborate with data scientists, BI developers, and analytics teams to ensure the smooth flow of data and insights across the organization.
  • Manage a team of data engineers, providing technical guidance and mentorship throughout the project lifecycle.
  • Engage with stakeholders and clients to align project deliverables with business goals.
  • Monitor and optimize data processing and storage to ensure efficiency and

Skills :

  • 5+ years of hands-on experience in data engineering, including leading data lake implementations and cloud-based solutions.
  • Proficiency in cloud platforms (AWS, Azure, or GCP) and services like Amazon S3, Azure Data Lake, Google Cloud Storage.
  • Extensive experience with data transformation tools such as Apache Spark, Databricks, AWS Glue, and Azure Data Factory.
  • Expertise in serverless architectures (e.g., AWS Lambda, Google Cloud Functions, Azure Functions).
  • Strong understanding of data governance, data quality, and security best practices in the cloud.
  • Familiarity with containerization and orchestration technologies such as Kubernetes and Docker.
  • Proficiency in SQL, Python, Scala, or Java for data manipulation and processing.
  • Experience working with data warehousing and analytics solutions like Amazon Redshift, Google BigQuery, or Azure Synapse.
  • Strong leadership and project management skills, with a track record of managing teams and delivering complex projects from pre-sales to delivery.
  • Excellent communication skills to effectively interact with stakeholders, clients, and technical teams.

Preferred Qualifications :

  • Experience with data governance tools like AWS Lake Formation, Azure Purview, or Google Data Catalog.
  • Certifications in cloud platforms such as AWS Certified Solutions Architect, Azure Data Engineer, or Google Professional Data Engineer.
  • Familiarity with CI/CD pipelines and DevOps practices in the context of data engineering.

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