Data Engineer

Overview

Remote
On Site
Depends on Experience
Contract - W2
Contract - 3 Year(s)
75% Travel
Able to Provide Sponsorship

Skills

Amazon DynamoDB
Amazon Kinesis
Apache Kafka
Apache Airflow
Collaboration
Attention To Detail
Apache Hadoop
Continuous Integration
Apache Hive
Apache Spark
Amazon S3
Amazon Web Services
Cloud Computing
Data Architecture
Big Data
Data Engineering
Communication
Data Integrity
Automated Testing
Conflict Resolution
Amazon Redshift
Data Modeling
Apache Cassandra
Continuous Delivery
Data Security
Extract, Transform, Load
Databricks
Electronic Health Record (EHR)
Machine Learning Operations (ML Ops)
Machine Learning (ML)
Good Clinical Practice
Git
Dimensional Modeling
Informatica
Management
Data Warehouse
Google Cloud Platform
MongoDB
Problem Solving
Talend
Snow Flake Schema
Storage
Scalability
Microsoft Azure
Regulatory Compliance
SQL
Scala
Workflow
Documentation
Java
Kubernetes
FOCUS
Stored Procedures
Meta-data Management
Performance Tuning
Real-time
Python
Database
Version Control
DevOps
ELT
Data Flow
NoSQL
Analytical Skill
Streaming
Docker

Job Details

Position: Data Engineer
Contract: W2 Only

Responsibilities

  • Design, develop, and maintain scalable data pipelines and architectures for ingestion, processing, and storage of large datasets.

  • Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and deliver reliable data solutions.

  • Build, optimize, and manage ETL/ELT workflows to extract, transform, and load data from multiple sources into data lakes or data warehouses.

  • Ensure data integrity, accuracy, and quality through validation, monitoring, and automated testing.

  • Work with cloud data platforms (AWS, Azure, or Google Cloud Platform) for modern data infrastructure development.

  • Implement best practices for data modeling, partitioning, and performance tuning.

  • Develop and maintain metadata management, lineage, and documentation for data assets.

  • Integrate data pipelines with APIs, streaming data sources, and third-party systems.

  • Collaborate with DevOps teams to automate deployments and monitor data systems using CI/CD pipelines.

  • Stay up to date with emerging data engineering tools, frameworks, and technologies.

Required Skills

  • 12+ years of experience as a Data Engineer or in a similar data-focused role.

  • Strong programming skills in Python, Java, or Scala.

  • Expertise in SQL (complex queries, performance tuning, stored procedures).

  • Hands-on experience with big data technologies such as Spark, Hadoop, Hive, or Kafka.

  • Proficiency with cloud data platforms such as AWS (Glue, Redshift, EMR, S3), Azure (Data Factory, Synapse), or Google Cloud Platform (BigQuery, Dataflow).

  • Experience building and maintaining ETL/ELT pipelines using tools like Informatica, Talend, dbt, or Apache Airflow.

  • Solid understanding of data warehousing concepts, dimensional modeling, and data architecture principles.

  • Familiarity with containerization (Docker, Kubernetes) and version control (Git).

  • Knowledge of CI/CD processes and DevOps practices for data projects.

  • Strong understanding of data security, governance, and compliance best practices.

Nice-to-Have

  • Experience with Snowflake, Databricks, or Redshift for modern data warehousing.

  • Exposure to real-time data streaming using Kafka, Kinesis, or Spark Streaming.

  • Familiarity with NoSQL databases (MongoDB, Cassandra, DynamoDB).

  • Experience with data cataloging and metadata management tools.

  • Knowledge of machine learning data pipelines and MLOps practices.

  • Cloud certifications (AWS Certified Data Engineer, Azure Data Engineer Associate, or Google Cloud Platform Professional Data Engineer).

Soft Skills

  • Strong analytical and problem-solving abilities with a data-driven mindset.

  • Excellent communication and collaboration skills with cross-functional teams.

  • Ability to work independently and manage multiple data projects simultaneously.

  • Detail-oriented with a focus on data accuracy, quality, and scalability.

  • Proactive, innovative, and passionate about modern data engineering practices.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.