Senior Data Engineer

Job Title:

Location:

Job Type :: Contract 2 Hire

Experience Required:

About the Role:

Senior Data Engineer

Key Responsibilities:

• Design and implement

  scalable, high-performance data pipelines

  for both batch and real-time processing.
• Architect and maintain

  data warehouse solutions

  leveraging modern frameworks and cloud-native services.
• Develop and optimize

  SQL queries

  and ensure efficient handling of various file formats such as

  Apache Parquet, Delta Lake, Apache Iceberg, or Hudi

  .
• Implement

  Change Data Capture (CDC) patterns

  for data consistency across systems.
• Build and maintain

  real-time data processing pipelines

  using

  Apache Flink, Kafka Streams, or PySpark

  .
• Manage workflow orchestration using

  Apache Airflow

  .
• Work with both

  relational and NoSQL database systems

  , applying deep knowledge of data modeling and warehousing concepts.
• Collaborate with stakeholders to translate business requirements into scalable data solutions.
• Stay updated with emerging technologies and industry best practices in the data ecosystem.

Required Skills & Qualifications:

• 8+ years

  of proven experience as a Data Engineer.
• Strong expertise in

  AWS Data Services

  (S3, Glue, Athena, EMR, Kinesis, etc.).
• Proficiency in

  SQL

  and strong analytical skills for data processing and optimization.
• Hands-on experience with

  distributed data processing frameworks

  like

  PySpark, Flink, or Kafka Streams

  .
• Deep knowledge of

  data warehousing concepts

  and modern

  architectural patterns

  .
• Expertise in

  workflow orchestration tools

  (preferably Apache Airflow).
• Experience with

  data integration tools

  and

  cloud-based data warehousing platforms

  .
• Excellent communication and interpersonal skills to work with both technical and non-technical teams.
• Ability to work independently in a fast-paced environment.

Why Join Us?

• Opportunity to work on

  cutting-edge data technologies

  .
• Collaborative work culture with

  end-to-end ownership

  of data projects.
• Competitive compensation and growth opportunities.