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If you are a

Sr.Data Engineer

looking for excitement, challenge and stability in your work, then you would be glad to come across this page.

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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.

/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.

BenefitsVisit us at http://alignity.io/careers. Alignity Solutions is an Equal Opportunity Employer, M/F/V/D.

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