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Senior Data Engineer

Raas Infotek LLCNewark, NJ🇺🇸United StatesPosted Sep 29, 2026

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
Newark, NJ, United States
Posted
Yesterday
DockerMicroservicesSQLAWSETLMachine LearningSnowflakeTableauAirflowApacheApache SparkAzureBigQueryCloudFormationDatabricksGenerative AIGitGoogle CloudKafkaKubernetesPower BIPythonRESTTerraform

Job Description

Senior Data Engineer 

Job Title: Senior Data Engineer / Lead Data Engineer
Experience: 12+ Years
Employment Type: W2

Job Description:
We are seeking an experienced Senior Data Engineer with 12+ years of experience designing, developing, and maintaining scalable data platforms and enterprise data pipelines.

Required Skills:

  • 12+ years of experience in Data Engineering / ETL / Data Warehousing
  • Strong expertise in Python, SQL, PySpark, and Apache Spark
  • Hands-on experience with AWS / Azure / Google Cloud Platform
  • Strong experience with Databricks, Snowflake, or BigQuery
  • Expertise in ETL/ELT pipeline development
  • Experience with Apache Airflow / Azure Data Factory / AWS Glue
  • Strong knowledge of data modeling, dimensional modeling, and data architecture
  • Experience with Kafka / event-driven data pipelines
  • Strong SQL optimization and performance tuning
  • Experience with CI/CD, Git, Docker, and DevOps practices
  • Experience working with large-scale structured and unstructured datasets
  • Knowledge of REST APIs, microservices, and cloud-native architectures
  • Experience with data quality, governance, security, and monitoring
  • Strong communication and stakeholder-management skills

Preferred Skills:

  • Machine Learning / AI data pipelines
  • Generative AI / RAG / Vector databases
  • Terraform or CloudFormation
  • Kubernetes
  • Power BI / Tableau
  • Experience in Banking, Healthcare, Insurance, or Retail domains

Key Responsibilities:

  • Design and develop scalable data pipelines and data platforms.
  • Build and optimize batch and real-time data processing solutions.
  • Develop ETL/ELT workflows using Python, SQL, Spark, and cloud services.
  • Implement data ingestion from APIs, databases, files, and streaming sources.
  • Design data models and enterprise data warehouses/lakes.
  • Improve pipeline performance, reliability, and data quality.
  • Collaborate with architects, developers, analysts, and business stakeholders.
  • Mentor junior and mid-level data engineers and provide technical leadership.

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