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  • Emplois similaires à : Data Engineer - AWS/Databricks - Mid Level
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Data Engineer - Databricks, AWSArtech • United States
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Data Engineer - Databricks, AWS

Artech
  • US
    United States
  • US
    United States
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À propos

Job ID :84867-1 Job Title: Data Engineer - Databricks, AWS Location: North Quincy,
Face to Face Interviews Duration: 6 months + possible extension Rate Range: $45- $49/hour on W2/ C2C (All inclusive)
Job Description: We are seeking an experienced
Senior Data Engineer
with strong expertise in
Databricks, AWS, Java, and Python
to design, develop, and optimize large-scale data platforms and pipelines. The ideal candidate will have extensive experience building cloud-native data solutions, leveraging Databricks on AWS, and implementing scalable data engineering frameworks that support analytics, AI/ML, and business intelligence initiatives.
Key Responsibilities: Design, develop, and maintain scalable data pipelines and ETL/ELT processes using
Databricks, Spark, and PySpark . Build and optimize cloud-native data solutions on
AWS . Develop robust applications and data services using
Java
and
Python . Architect and manage large-scale data platforms supporting enterprise analytics and reporting. Collaborate with data scientists, analysts, and business stakeholders to deliver data-driven solutions. Implement data governance, security, and compliance best practices across cloud environments. Optimize data processing performance, scalability, and cost efficiency. Support AI/ML initiatives by preparing and engineering datasets for model training and deployment. Monitor, troubleshoot, and enhance data platform reliability and performance. Participate in architecture reviews and provide technical leadership on data engineering best practices. Required Skills:
10+ years of experience in
Software Engineering and Data Engineering . Strong hands-on development experience with
Java
and
Python . Extensive experience in
Data Engineering
and large-scale distributed data platforms. Deep expertise with
Databricks on AWS , including:
Apache Spark PySpark Delta Lake Data Lakehouse Architecture
Strong knowledge of
AWS services
such as S3, Lambda, Glue, EMR, IAM, Redshift, and EC2. Experience designing and implementing cloud-native architectures. Strong understanding of data security, governance, and compliance frameworks. Experience with CI/CD, version control, and DevOps practices. Excellent problem-solving and communication skills. Preferred Qualifications:
Experience applying
AI/ML tools and techniques
within enterprise environments. Knowledge of real-time data processing and streaming technologies. Experience with data modeling, data warehousing, and analytics platforms. AWS or Databricks certifications are highly preferred. Company Benefits & Culture
Competitive salary and benefits package. Collaborative and supportive work environment. Opportunities for professional development and growth.
  • United States

Compétences linguistiques

  • English
Avis aux utilisateurs

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