Data Engineer
Pittsburgh, Pennsylvania, United States of America
Contract
3 days ago
Key skills
PythonSQLNoSQLETLELTData EngineeringData WarehousingAnalyticsSnowflakeRedshiftDatabricksSparkApache SparkKafkaAirflowAWSAzureGoogle CloudTerraformGitVersion ControlCI/CD
About this role
Job Title: Data Engineer
Location: Pittsburgh, PA, New York City, NY, Jersey City, NJ, Tampa, FL, Boston, MA
Duration:12+ Months Contract
NO C2C Only W2
Job Summary:
We are seeking an experienced Data Engineer to design, develop, and maintain scalable data pipelines and cloud-based data platforms. The ideal candidate will have strong expertise in data engineering, ETL/ELT processes, cloud technologies, big data frameworks, and data warehousing solutions. This role will work closely with business stakeholders, data analysts, architects, and development teams to deliver reliable, high-performance data solutions that support enterprise analytics and reporting initiatives.
Key Responsibilities:
Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
Build and optimize data ingestion, transformation, and integration processes.
Develop cloud-native data solutions using AWS, Azure, or Google Cloud Platform.
Design and implement data models, data lakes, and data warehouses.
Ensure data quality, governance, security, and compliance standards.
Optimize database performance and query execution for large-scale datasets.
Implement data monitoring, validation, and troubleshooting processes.
Collaborate with Data Scientists, Analysts, and Business Teams to support analytics initiatives.
Automate data workflows and deployments using CI/CD best practices.
Support real-time and batch data processing architectures.
Required Skills:
Strong experience with Python, SQL, and Data Engineering concepts.
Hands-on experience with ETL/ELT development.
Experience with Apache Spark, PySpark, or Databricks.
Knowledge of Data Warehousing concepts and dimensional modeling.
Experience with cloud platforms: AWS, Azure, or Google Cloud Platform.
Experience with data orchestration tools such as Airflow.
Experience working with relational and NoSQL databases.
Knowledge of data lakes and big data technologies.
Strong understanding of performance tuning and optimization.
Experience with version control systems such as Git.
Preferred Qualifications:
Experience with Snowflake, Databricks, or Redshift.
Knowledge of Kafka or real-time streaming technologies.
Experience with Terraform or Infrastructure as Code (IaC).
Familiarity with DevOps and CI/CD pipelines.
Experience supporting enterprise-scale data platforms.
Relevant cloud certifications are a plus.
Best Regards,
Teresa Rose
Teresa Rose