Data Engineering Manager

This is a fully remote position, open to applicants in India.

📋 Description

• Lead and guide a team of data engineers.

• Establish and advance the overarching data architecture strategy.

• Supervise the design and execution of data ingestion frameworks and integration solutions.

• Create and maintain CI/CD pipelines.

• Work closely with clients and internal stakeholders.

• Serve as a trusted advisor to clients.

• Ensure compliance with data governance and security standards.

• Promote the adoption of DevOps/DataOps principles within the team.

• Manage project priorities and delivery schedules.

⛳️ Requirements

• 10-13 years of pertinent experience in data architecture design and execution.

• Demonstrated leadership experience overseeing data engineering and architecture teams in complex enterprise settings.

• In-depth knowledge of AWS services, including S3, EC2, Glue, Lambda, and Secrets Manager.

• Practical experience with Databricks for unified data analytics.

• Proficient in DBT (Data Build Tool).

• Experienced in using Apache Airflow for workflow automation and pipeline management.

• Strong programming abilities in Python, PySpark, Spark, and Scala.

• Familiar with software version control and CI/CD tools such as Git, Jenkins, and Apache Subversion.

• AWS certifications or other equivalent professional technical certifications are highly desirable.

• Knowledge of cloud and on-premises middleware and enterprise integration technologies.

• Expertise in writing and optimizing Spark jobs and designing data warehouse solutions.

• Excellent analytical skills with advanced SQL proficiency.

• Experience managing large-scale data warehousing environments and complex ETL/ELT pipelines.

• Strong grasp of data modeling concepts, data governance, and data quality frameworks.

• Outstanding communication skills, with a proven ability to engage and influence clients and stakeholders.

• Experience in Python and/or Java development in the contexts of data engineering and architecture.

• Familiarity with Big Data ecosystems, including EMR, Hadoop, Databricks, Hive, and Pyspark.

🏝️ Benefits

• Competitive salary.

• Flexible working hours.

• Professional development budget.

• Home office setup allowance.

• Global team events.