Data Engineer w AWS services such as AWS Glue, Lambda, Athena, Step Functions, and Lake

Intermedia Group-posted about 2 months ago
$140,000 - $185,000/Yr
Full-time • Mid Level
Hybrid • Ridgefield, CT
11-50 employees
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We are seeking a highly skilled and experienced Data Engineer to design, build, and maintain our scalable and robust data infrastructure on a cloud platform. In this pivotal role, you will be instrumental in enhancing our data infrastructure, optimizing data flow, and ensuring data availability. You will be responsible for both the hands-on implementation of data pipelines and the strategic design of our overall data architecture. Seeking a candidate with hands-on experience with AWS services such as AWS Glue, Lambda, Athena, Step Functions, and Lake, Proficiency in Python and SQL and DevOps/CI/CD experience

  • Design, develop, and maintain scalable data pipelines and ETL processes to support data integration and analytics.
  • Collaborate with data architects, modelers and IT team members to help define and evolve the overall cloud-based data architecture strategy, including data warehousing, data lakes, streaming analytics, and data governance frameworks
  • Collaborate with data scientists, analysts, and other business stakeholders to understand data requirements and deliver solutions.
  • Optimize and manage data storage solutions (e.g., S3, Snowflake, Redshift) ensuring data quality, integrity, security, and accessibility.
  • Implement data quality and validation processes to ensure data accuracy and reliability.
  • Develop and maintain documentation for data processes, architecture, and workflows.
  • Monitor and troubleshoot data pipeline performance and resolve issues promptly.
  • Consulting and Analysis: Meet regularly with defined clients and stakeholders to understand and analyze their processes and needs. Determine requirements to present possible solutions or improvements.
  • Technology Evaluation: Stay updated with the latest industry trends and technologies to continuously improve data engineering practices.
  • Cloud Expertise: Expert-level proficiency in at least one major cloud platform (AWS, Azure, or GCP) with extensive experience in their respective data services (e.g., AWS S3, Glue, Lambda, Redshift, Kinesis; Azure Data Lake, Data Factory, Synapse, Event Hubs; GCP BigQuery, Dataflow, Pub/Sub, Cloud Storage); experience with AWS data cloud platform preferred
  • SQL Mastery: Advanced SQL writing and optimization skills.
  • Data Warehousing: Deep understanding of data warehousing concepts, Kimball methodology, and various data modeling techniques (dimensional, star/snowflake schemas).
  • Big Data Technologies: Experience with big data processing frameworks (e.g., Spark, Hadoop, Flink) is a plus.
  • Database Systems: Experience with relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, Cassandra).
  • DevOps/CI/CD: Familiarity with DevOps principles and CI/CD pipelines for data solutions.
  • Hands-on experience with AWS services such as AWS Glue, Lambda, Athena, Step Functions, and Lake Formation
  • Proficiency in Python and SQL
  • 4+ years of progressive experience in data engineering, with a significant portion dedicated to cloud-based data platforms.
  • ETL/ELT Tools: Hands-on experience with ETL/ELT tools and orchestrators (e.g., Apache Airflow, Azure Data Factory, AWS Glue, dbt).
  • Data Governance: Understanding of data governance, data quality, and metadata management principles.
  • AWS Experience: Ability to evaluate AWS cloud applications, make architecture recommendations; AWS solutions architect certification (Associate or Professional) is a plus
  • Familiarity with Snowflake
  • Knowledge of dbt (data build tool)
  • Strong problem-solving skills, especially in data pipeline troubleshooting and optimization
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