OverviewData Engineer Manager ResponsibilitiesData Engineering LeadershipLead and mentor a team of data engineers in developing and managing scalable, secure, and high-performance data pipelines.Define best practices for data ingestion, transformation, and processing in a Lakehouse architecture.Driv
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Data Engineering manager
Job Description:
Overview

Data Engineer Manager


Responsibilities

Data Engineering Leadership

  • Lead and mentor a team of data engineers in developing and managing scalable, secure, and high-performance data pipelines.
  • Define best practices for data ingestion, transformation, and processing in a Lakehouse architecture.
  • Drive automation, performance tuning, and cost optimization in cloud data solutions.

Cloud Data Infrastructure & Processing

  • Architect and manage AWS-based big data solutions (EMR, EKS, Glue, Redshift).
  • Design and maintain Apache Airflow workflows for data orchestration.
  • Optimize Spark and distributed data processing frameworks for large-scale workloads.
  • Implement streaming solutions (Kafka, Kinesis, Flink) for real-time data processing.

AI/ML & Advanced Analytics

  • Collaborate with Data Scientists and AI/ML teams to build and deploy machine learning models using AWS SageMaker.
  • Support feature engineering, model training, and inference pipelines at scale.
  • Enable AI-driven analytics by integrating structured and unstructured data sources.

Business Intelligence & Visualization

  • Support BI and reporting teams with optimized data models for Amazon QuickSight and other visualization tools.
  • Ensure efficient data aggregation and pre-processing for interactive dashboards and self-service analytics.
  • Design, develop, and maintain middleware components that facilitate seamless communication between data platforms, applications, and analytics layers.

Master Data Management (MDM) & Governance

  • Implement MDM strategies to ensure clean, consistent, and deduplicated data.
  • Establish data governance policies for security, privacy, and compliance (GDPR, HIPAA, etc.).
  • Ensure adherence to data quality frameworks across structured and unstructured datasets.

Collaboration & Strategy

  • Partner with business teams, AI/ML teams, and analysts to deliver high-value data products.
  • Define and maintain data architecture strategies aligned with business goals.
  • Enable real-time and batch processing for analytics, reporting, and AI-driven insights.


    Technical Expertise:

    • Extensive AWS experience with services such as EMR, EKS, Glue, Redshift, S3, Lambda, and SageMaker.
    • Proficient in big data processing frameworks (e.g., Spark, Hive, Presto) and Lakehouse architectures.
    • Skilled in designing and managing Apache Airflow workflows and other orchestration tools.
    • Solid understanding of Master Data Management (MDM) and data governance best practices.
    • Proficient with SQL & NoSQL databases (e.g., Redshift, DynamoDB, PostgreSQL, Elasticsearch).
    • Middleware Development – Proven expertise in building middleware components like REST API that integrate data pipelines with applications, analytics platforms, and real-time systems.
    • Hands-on experience with Gitlab CI/CD, Terraform, CFT, and Infrastructure-as-Code (IaC) methodologies.
    • Familiarity with AI/ML pipelines, model deployment, and monitoring using SageMaker.
    • Experience with data visualization tools, particularly AWS QuickSight, for business intelligence.

Qualifications

Experience with Lakehouse frameworks (Glue Catalog, Iceberg, Delta Lake).
Expertise in streaming data solutions (Kafka, Kinesis, Flink).
In-depth understanding of security best practices in AWS data architectures.
Demonstrated success in driving AI/ML initiatives from ideation to production.

Educational Qualification:

  • Bachelor’s degree or higher (UG+) in Computer Science, Data Engineering, Aerospace Engineering, or a related field.
  • Advanced degrees (Master’s, PhD) in Data Science or AI/ML are a plus.
REQ-145778","qualifications":"

Experience with Lakehouse frameworks (Glue Catalog, Iceberg, Delta Lake).
Expertise in streaming data solutions (Kafka, Kinesis, Flink).
In-depth understanding of security best practices in AWS data architectures.
Demonstrated success in driving AI/ML initiatives from ideation to production.

Educational Qualification:

  • Bachelor’s degree or higher (UG+) in Computer Science, Data Engineering, Aerospace Engineering, or a related field.
  • Advanced degrees (Master’s, PhD) in Data Science or AI/ML are a plus.
Company Details
Panasonic Avionics Corporation
Corporate Office
26200 Enterprise Way
Lake Forest, California 92630-8400 USA
www.panasonic.aero
157 Open Jobs Available
Panasonic Avionics is the world leader in in-flight entertainment and communications, with most systems installed, most airlines served, and the industries deepest knowledge base, developed with over 25 years of consistent product innovation and committed...

Benefits:
DOE
(Job and company information not to be copied, shared, scraped, or otherwise disseminated/distributed without explicit consent of JSfirm, LLC)
Job Info
Location
Pune, Maharashtra, India
Type
Permanent
Company Details
Panasonic Avionics Corporation
Corporate Office
26200 Enterprise Way
Lake Forest, California 92630-8400 USA
www.panasonic.aero
157 Open Jobs Available
Panasonic Avionics is the world leader in in-flight entertainment and communications, with most systems installed, most airlines served, and the industries deepest knowledge base, developed with over 25 years of consistent product innovation and committed...

Benefits:
DOE

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