Senior Data Engineer

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Requirements

Role: Sr.Data Engineer

Location:Orlando,FL

Exp: 10+ Years

Requirements

We are seeking a highly skilled Senior Data Engineer with 10+ years of experience to join our team and support large-scale data initiatives. This role demands deep expertise in Snowflake , Python , DBT , and AWS services, along with proven experience in building robust, scalable ELT pipelines using tools like Apache Airflow . The ideal candidate is a strong communicator , independent contributor , and 100% hands-on in all relevant technologies.

Key Responsibilities:

• Design, develop, and maintain ELT data pipelines using Apache Airflow, DBT, and Snowflake in an AWS environment.
  

• Write modular, production-grade Python code for data ingestion, transformation, and automation tasks.
  

• Develop complex DBT models (incremental models, snapshots) with reusable macros and documentation.
  

• Implement data pipeline orchestration and job scheduling using Apache Airflow (MWAA) .
  

• Optimize SQL queries and Snowflake performance (partitioning, clustering, caching).
  

• Integrate and process data from multiple sources, including REST APIs .
  

• Set up and maintain monitoring and logging using AWS CloudWatch .
  

• Follow best practices for cloud security , including IAM roles, encryption, and access control.
  

• Participate in version control and CI/CD processes using Git .
  

• Collaborate with cross-functional teams in a client-facing capacity.
  

Required Technical Skills:

Data Engineering & ELT:

• Strong experience with Snowflake (data modeling, optimization, clustering, caching).
  

• Deep SQL expertise (complex joins, CTEs, window functions, subqueries, performance tuning).
  

• Proficient with DBT (Data Build Tool) :
  

  • Creating and managing DBT models, macros, tests, and documentation.
    

  • Version controlling with Git and setting up CI/CD for DBT pipelines.
    

Programming:

• Strong hands-on skills in Python :
  

  • Use of Pandas, NumPy for data manipulation.
    

  • Scripting for automation and API integration.
    

  • Writing custom Jinja/DBT macros and conditional logic.
    

AWS Cloud Platform:

• AWS S3 (data lake architecture, security best practices).
  

• AWS Lambda (serverless compute for lightweight ETL tasks).
  

• AWS Redshift (data warehousing, performance optimization).
  

• AWS Glue (ETL orchestration – nice to have ).
  

• Amazon Athena (querying S3 using SQL – nice to have ).
  

• IAM (access control), KMS/encryption, and best practices for cloud security.
  

• AWS CloudWatch (monitoring, alerting for Airflow and data pipeline failures).
  

Workflow Orchestration:

• Expertise in Apache Airflow (preferably MWAA) :
  

  • DAG creation and monitoring.
    

  • Integration with DBT, S3, Redshift, and external APIs.
    

Must-Have Qualifications:

• 10+ years of overall IT experience with at least 5 years in Data Engineering.
  

• Client-facing experience with excellent verbal and written communication.
  

• Ability to work independently with minimal supervision (Individual Contributor).
  

• Proven track record of delivering large-scale ELT solutions in cloud environments.
  

Preferred/Optional Experience:

• Experience with MWAA (Managed Workflows for Apache Airflow) .
  

• Familiarity with AWS Glue for ETL development.
  

• Understanding of data governance and quality frameworks.
  

• Familiarity with financial domain data structures, compliance, and reporting.
  

Soft Skills:

• Problem-solving mindset and attention to detail.
  

• Strong documentation and organizational skills.
  

• Comfortable collaborating in agile/scrum teams.
  

Benefits

Visit us at . Alignity Solutions is an Equal Opportunity Employer, M/F/V/D.

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