Overview
On Site
Full Time
Job Details
Job Summary
Location: Reston VA
Experience: Minimum 7 years in data engineering
Job Type: Permanent
Ideal Candidate Should Have
Expertise in Databricks on AWS, including Delta Lake, Databricks SQL, and Databricks Workflows.
Proficiency in Python, Java, or Scala for data processing and pipeline development.
Experience with Apache Spark, Hadoop, or similar big data processing frameworks.
Strong understanding of ETL tools (e.g., Fivetran, Apache Airflow, MuleSoft).
Hands-on experience with Infrastructure as Code (IaC) tools such as Terraform.
Deep knowledge of SQL and familiarity with relational (SQL Server, MySQL, PostgreSQL) and NoSQL databases (MongoDB, Cassandra).
Experience with AWS cloud-based data services, including Redshift.
Strong grasp of data warehousing concepts, data modeling, and schema design.
Experience with containerization (Docker, Kubernetes).
Ability to mentor junior engineers and collaborate across teams.
Relevant certifications (AWS, Databricks) are a plus.
Job Description
Thinking Minds Inc.'s client is seeking a Senior Data Engineer to design, develop, and maintain scalable data infrastructures in AWS Cloud. The role requires building robust ETL pipelines, data architectures, and cloud-based analytics platforms. The ideal candidate will collaborate with data scientists, analysts, and business teams to ensure seamless data accessibility, reliability, and security.
Key Responsibilities
Design and develop scalable data pipelines for efficient data ingestion, transformation, and storage
Build and optimize data architectures such as data lakes, data warehouses, and databases
Implement and maintain data integration solutions via APIs and data connectors
Ensure data integrity, governance, and security using industry best practices
Monitor and troubleshoot data pipelines to maintain high availability and performance
Collaborate with data scientists, analysts, and business stakeholders to meet data needs
Utilize Databricks on AWS, including Delta Lake, Databricks SQL, and Workflows
Lead and mentor junior data engineers in best practices and technical development
Stay updated with emerging data technologies and recommend system improvements
Document key data engineering processes, architectures, and workflows
Required Qualifications:
Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field
7+ years of experience in data engineering
Proficiency in Databricks on AWS, Apache Spark, and Hadoop
Strong programming skills in Python, Java, or Scala
Hands-on experience with ETL tools (Fivetran, Apache Airflow, MuleSoft)
Experience with Infrastructure as Code (Terraform)
Expertise in SQL and database management (relational & NoSQL)
Familiarity with AWS cloud data services (e.g., Redshift)
Knowledge of data warehousing concepts, schema design, and data modeling
Experience with containerization (Docker, Kubernetes) is a plus
Strong communication skills with the ability to convey technical concepts to non-technical stakeholders
Relevant certifications (AWS, Databricks) are preferred
Location: Reston VA
Experience: Minimum 7 years in data engineering
Job Type: Permanent
Ideal Candidate Should Have
Expertise in Databricks on AWS, including Delta Lake, Databricks SQL, and Databricks Workflows.
Proficiency in Python, Java, or Scala for data processing and pipeline development.
Experience with Apache Spark, Hadoop, or similar big data processing frameworks.
Strong understanding of ETL tools (e.g., Fivetran, Apache Airflow, MuleSoft).
Hands-on experience with Infrastructure as Code (IaC) tools such as Terraform.
Deep knowledge of SQL and familiarity with relational (SQL Server, MySQL, PostgreSQL) and NoSQL databases (MongoDB, Cassandra).
Experience with AWS cloud-based data services, including Redshift.
Strong grasp of data warehousing concepts, data modeling, and schema design.
Experience with containerization (Docker, Kubernetes).
Ability to mentor junior engineers and collaborate across teams.
Relevant certifications (AWS, Databricks) are a plus.
Job Description
Thinking Minds Inc.'s client is seeking a Senior Data Engineer to design, develop, and maintain scalable data infrastructures in AWS Cloud. The role requires building robust ETL pipelines, data architectures, and cloud-based analytics platforms. The ideal candidate will collaborate with data scientists, analysts, and business teams to ensure seamless data accessibility, reliability, and security.
Key Responsibilities
Design and develop scalable data pipelines for efficient data ingestion, transformation, and storage
Build and optimize data architectures such as data lakes, data warehouses, and databases
Implement and maintain data integration solutions via APIs and data connectors
Ensure data integrity, governance, and security using industry best practices
Monitor and troubleshoot data pipelines to maintain high availability and performance
Collaborate with data scientists, analysts, and business stakeholders to meet data needs
Utilize Databricks on AWS, including Delta Lake, Databricks SQL, and Workflows
Lead and mentor junior data engineers in best practices and technical development
Stay updated with emerging data technologies and recommend system improvements
Document key data engineering processes, architectures, and workflows
Required Qualifications:
Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field
7+ years of experience in data engineering
Proficiency in Databricks on AWS, Apache Spark, and Hadoop
Strong programming skills in Python, Java, or Scala
Hands-on experience with ETL tools (Fivetran, Apache Airflow, MuleSoft)
Experience with Infrastructure as Code (Terraform)
Expertise in SQL and database management (relational & NoSQL)
Familiarity with AWS cloud data services (e.g., Redshift)
Knowledge of data warehousing concepts, schema design, and data modeling
Experience with containerization (Docker, Kubernetes) is a plus
Strong communication skills with the ability to convey technical concepts to non-technical stakeholders
Relevant certifications (AWS, Databricks) are preferred
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.