Senior Data Engineer

Senior Data Engineer

Location: Edison, NJ (Hybrid)

Contract: W2 Only

Duration: 12+ Months

About the Opportunity

We are looking for a highly skilled Senior Data Engineer to join our team in Edison, New Jersey. This pivotal role will be responsible for designing and implementing enterprise-grade data solutions, developing robust ETL pipelines, and driving our data strategy forward. The ideal candidate will bring deep expertise across multiple cloud platforms, data visualization tools, and database technologies to build scalable, secure, and efficient data ecosystems.

Key Responsibilities

• Design and implement end-to-end data architecture solutions aligned with business objectives and industry best practices
• Develop and maintain enterprise data models, data dictionaries, and architecture documentation
• Define data standards, policies, and governance frameworks to ensure data quality and compliance
• Evaluate emerging technologies and recommend solutions to enhance data capabilities
• Create roadmaps for data platform modernization and cloud migration initiatives
• Design, develop, and maintain scalable ETL/ELT pipelines for data ingestion, transformation, and loading
• Build and optimize data warehousing solutions to support analytics and reporting needs
• Implement data integration solutions across multiple source systems and platforms
• Develop automated data quality checks, validation rules, and monitoring processes
• Optimize query performance and troubleshoot data pipeline issues
• Collaborate with business stakeholders to design and develop Tableau and Power BI dashboards and reports
• Create semantic layers, data models, and calculated fields to support self-service analytics
• Establish visualization standards and best practices across the organization
• Train and support business users on BI tools and data interpretation
• Design and manage Oracle and PostgreSQL database environments
• Implement database optimization strategies including indexing, partitioning, and query tuning
• Ensure database security, backup, recovery, and disaster recovery procedures
• Monitor database performance and proactively address issues
• Establish and enforce data governance policies and procedures
• Implement data lineage, metadata management, and data cataloging solutions
• Manage data access controls, security protocols, and audit processes
• Architect and implement data solutions on AWS, Azure, and/or Google Cloud Platform
• Leverage cloud-native services for data storage, processing, and analytics
• Optimize cloud infrastructure for cost efficiency and performance
• Implement cloud security best practices and compliance controls
• Mentor junior data engineers and provide technical guidance
• Collaborate with cross-functional teams including IT, business analysts, and data scientists
• Lead technical discussions and present solutions to stakeholders and leadership
• Participate in Agile ceremonies and contribute to sprint planning

Required Qualifications

• 14+ years of progressive experience in data engineering, with experience in a senior or lead technical role
• Proven experience designing and implementing enterprise data solutions
• Strong hands-on experience with AWS (Redshift, Glue, S3, Lambda, EMR, Athena)
• Proficiency in Microsoft Azure (Azure Data Factory, Synapse Analytics, Data Lake, Databricks)
• Experience with Google Cloud Platform (BigQuery, Dataflow, Cloud Storage, Pub/Sub)
• Expert-level experience with ETL tools such as Informatica, Talend, SSIS, AWS Glue, Azure Data Factory, or Apache Airflow
• Strong understanding of ETL best practices, data transformation patterns, and scheduling
• Advanced proficiency in Tableau (Desktop, Server, Prep)
• Strong experience with Power BI (Desktop, Service, DAX, Power Query)
• Ability to create compelling data visualizations and executive dashboards
• Expert-level SQL skills with query optimization experience
• Deep knowledge of Oracle database (PL/SQL, performance tuning, administration)
• Strong experience with PostgreSQL (configuration, optimization, replication)
• Experience with modern data warehousing platforms (Snowflake, Redshift, Synapse, BigQuery)
• Proficiency in dimensional modeling, star/snowflake schemas, and data vault methodologies
• Experience implementing data governance frameworks and tools
• Knowledge of data cataloging solutions (Collibra, Alation, AWS Glue Catalog)
• Experience with data quality tools and frameworks
• Proficiency in Python for data engineering and automation
• Experience with SQL scripting and stored procedures
• Familiarity with Scala, Java, or PySpark is a plus
• Version control systems (Git, GitHub, Bitbucket)
• Infrastructure as Code (Terraform, CloudFormation)
• CI/CD pipelines for data workflows
• Understanding of data security and encryption standards

Preferred Qualifications

• Cloud certifications (AWS Certified Data Analytics, Azure Data Engineer Associate, Google Cloud Platform Professional Data Engineer)
• Knowledge of real-time streaming technologies (Kafka, Kinesis, Event Hubs)
• Experience with dbt (data build tool) for transformation workflows
• Familiarity with machine learning pipelines and MLOps
• Experience with container technologies (Docker, Kubernetes)