Senior Data Engineer

Hybrid in Boston, MA, US • Posted 3 hours ago • Updated 3 hours ago
Contract W2
12 Months
No Travel Required
On-site
$60 - $70/hr
Fitment

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Job Details

Skills

  • Amazon Redshift
  • Agile
  • Amazon Web Services
  • Apache Hadoop
  • Apache Kafka
  • Apache Spark
  • Artificial Intelligence
  • Big Data
  • Cloud Computing
  • Conflict Resolution
  • Data Engineering
  • Data Analysis
  • Data Governance
  • Data Modeling
  • Snow Flake Schema
  • Scrum
  • SQL
  • Scala
  • Python
  • MySQL
  • Microsoft SSIS
  • Microsoft Azure
  • Machine Learning Operations (ML Ops)
  • Kubernetes
  • Jenkins
  • Java
  • PL/SQL
  • PostgreSQL
  • Git
  • ELT
  • Docker
  • DevOps
  • Generative Artificial Intelligence (AI)
  • GitHub
  • HIPAA
  • GitLab
  • Good Clinical Practice
  • Machine Learning (ML)
  • Databricks
  • Database
  • Extract, Transform, Load

Summary

Job Summary

We are seeking an experienced Senior Data Engineer with 12+ years of expertise in designing, developing, and maintaining scalable data platforms, data pipelines, and enterprise data solutions. The ideal candidate will have strong experience in cloud-based data architectures, ETL/ELT processes, data warehousing, big data technologies, and data governance. This role requires close collaboration with business stakeholders, data scientists, analysts, and engineering teams to deliver high-quality data solutions that support strategic business initiatives.

Key Responsibilities

  • Design, develop, and optimize scalable data pipelines for batch and real-time data processing.
  • Build and maintain enterprise data warehouses, data lakes, and lakehouse architectures.
  • Develop ETL/ELT workflows to ingest, transform, validate, and load data from multiple sources.
  • Implement data integration solutions across on-premises and cloud environments.
  • Collaborate with business analysts, product owners, and stakeholders to understand data requirements and translate them into technical solutions.
  • Ensure data quality, integrity, security, and governance across data platforms.
  • Optimize database performance, query execution, and data processing frameworks.
  • Develop and maintain data models, metadata repositories, and data dictionaries.
  • Support advanced analytics, machine learning, and AI initiatives by providing reliable data infrastructure.
  • Monitor and troubleshoot data pipelines, ensuring high availability and performance.
  • Implement CI/CD practices and automation for data engineering workflows.
  • Mentor junior engineers and establish best practices for data engineering development.
  • Participate in architecture reviews, technical design discussions, and strategic planning initiatives.

Required Qualifications

  • Bachelor''s degree in Computer Science, Information Technology, Engineering, or a related field.
  • 12+ years of experience in Data Engineering, Data Warehousing, or Big Data development.
  • Strong experience with SQL and relational databases such as Oracle, SQL Server, PostgreSQL, or MySQL.
  • Extensive experience building ETL/ELT pipelines using tools such as Informatica, Talend, DataStage, SSIS, or Matillion.
  • Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
  • Experience with modern data warehousing solutions including Snowflake, Redshift, Synapse Analytics, or BigQuery.
  • Strong programming skills in Python, Scala, Java, or Spark.
  • Experience with Apache Spark, Hadoop ecosystem, Kafka, and distributed data processing frameworks.
  • Expertise in data modeling techniques including dimensional modeling and Data Vault.
  • Experience with workflow orchestration tools such as Airflow, Azure Data Factory, or AWS Glue.
  • Strong understanding of data governance, data quality, and master data management concepts.
  • Experience with Git, CI/CD pipelines, and DevOps practices.

Preferred Qualifications

  • Experience with Databricks and Lakehouse architecture.
  • Knowledge of machine learning data pipelines and MLOps concepts.
  • Experience implementing real-time streaming solutions using Kafka, Spark Streaming, or Flink.
  • Familiarity with containerization technologies such as Docker and Kubernetes.
  • Cloud certifications such as AWS Certified Data Analytics, Azure Data Engineer Associate, or Google Professional Data Engineer.
  • Experience working in Agile/Scrum environments.

Technical Skills

Programming Languages: Python, SQL, Scala, Java
Cloud Platforms: AWS, Azure, Google Cloud Platform
Data Warehousing: Snowflake, Redshift, Synapse, BigQuery
Big Data Technologies: Spark, Hadoop, Hive, Kafka, Flink
ETL/ELT Tools: Informatica, Talend, DataStage, SSIS, Matillion, dbt
Orchestration Tools: Airflow, Azure Data Factory, AWS Glue
Databases: Oracle, SQL Server, PostgreSQL, MySQL, MongoDB
Version Control: Git, GitHub, GitLab, Bitbucket
DevOps: Jenkins, Azure DevOps, Docker, Kubernetes

Soft Skills

  • Strong analytical and problem-solving abilities.
  • Excellent communication and stakeholder management skills.
  • Ability to work independently and lead technical initiatives.
  • Strong mentoring and leadership capabilities.
  • Experience collaborating with cross-functional teams in fast-paced environments.

Nice to Have:

  • Data Mesh and Data Fabric architecture experience.
  • AI/ML data engineering experience.
  • Experience with Generative AI data platforms and vector databases.
  • Knowledge of regulatory compliance standards such as GDPR, HIPAA, or SOX.
 
 
 
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.
  • Dice Id: 10477291
  • Position Id: 9007512
  • Posted 3 hours ago
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