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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