Senior Data Engineer 1

Ridgeway, AK - USA

Monthly Salary: Not Disclosed

Posted on: 5 days ago

Vacancies: 1 Vacancy

Job Summary

Title: Senior Data Engineer
Location: Ridgefield CT (Onsite)
Duration: Fulltime

Duties & Responsibilities

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.

Requirements

Associate degree in Computer Science MIS or related field with a minimum of 8 years experience; or bachelors degree in computer science or MIS or related field with minimum of 4years of experience; or a masters degree in computer science MIS or related field with minimum 2 years of experience; or relevant Business or IT experience of minimum of 4 years.

Must-Have Skills

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

Desired Skills

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

Title: Senior Data Engineer Location: Ridgefield CT (Onsite) Duration: Fulltime Duties & Responsibilities 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 def...

Title: Senior Data Engineer
Location: Ridgefield CT (Onsite)
Duration: Fulltime

Duties & Responsibilities

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.

Requirements

Associate degree in Computer Science MIS or related field with a minimum of 8 years experience; or bachelors degree in computer science or MIS or related field with minimum of 4years of experience; or a masters degree in computer science MIS or related field with minimum 2 years of experience; or relevant Business or IT experience of minimum of 4 years.

Must-Have Skills

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

Desired Skills

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