Associate Data and AI Engineer

Jobtailor

Hartford (CT)

On-site

USD 110,000 - 160,000

Full time

5 days ago

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Job summary

Jobtailor is seeking a data engineering professional to design and implement robust data pipelines for predictive and AI-centric applications. You will collaborate with cross-functional teams, translate complex requirements into scalable solutions, and ensure data quality and lineage across cloud platforms, using Python, SQL, and modern orchestration tooling.

The role emphasizes real-time and batch modeling, automation, and maintaining repeatable code artifacts in GitHub, with exposure to

Qualifications

Must be authorized to work in the U.S. now and in the future.
Bachelor’s degree in Computer Science, Engineering, IT, MIS, or related discipline.
Experience developing solutions using Python and SQL.
Experience using AI code assistants as part of daily workflow.
Familiarity with GitHub.
Familiarity with Agile teams, creating user stories, and planning/managing work.
Exposure to data ingestion from relational databases, Hadoop/Spark, cloud data sources, XML, JSON, CSV, Parquet.
Exposure to ETL concepts, metadata management, and data validation.
Exposure to automation tools such as Autosys, Cron, or Airflow.
Exposure to GCP or AWS services is a plus.
Exposure to IaC tools like CloudFormation, Terraform, TeamCity, Jenkins, Octopus.
Exposure to cloud data warehouses like Snowflake, Redshift, or BigQuery is a plus.
Able to communicate effectively with technical and non-technical teams.
Able to translate complex technical topics into business solutions and strategies.
Must be authorized to work in the US without company sponsorship.
Company will not support STEM OPT endorsement for this position.

Responsibilities

Implement data pipelines integrating structured, semi-structured, and unstructured data for Predictive, AI, and Agentic solutions.
Build and maintain scalable ML- and AI-driven systems using Snowflake, REST APIs, AWS, or GCP infrastructure.
Collaborate with Enterprise Data, IT, Cloud Enablement, and Enterprise Architecture teams and external partners.
Translate business requests into technical requirements for small and medium-complexity engineering tasks.
Validate internal and external data sources for availability and quality.
Work with subject matter experts to describe and understand data lineage and suitability for use cases.
Develop code enabling real-time modeling solutions to be ingested into front-end systems.
Develop batch solutions implemented through modern scheduling and orchestration tools.
Produce reproducible code artifacts and documentation using GitHub for handoff to other teams.
Ensure reliability, availability, and scalability through monitoring, alerting, and incident management.
Collaborate with AI Ops and infrastructure teams on deployment, operation, and maintenance of AI/ML systems.

Skills

Python Development

SQL Proficiency

Data Pipeline Implementation

Cloud Infrastructure (AWS, GCP)

Agile Methodology

Education

Bachelor’s degree in Computer Science, Engineering, IT, MIS

Tools

Snowflake

REST APIs

CloudFormation

Terraform

TeamCity

Jenkins

Octopus

Hadoop

Spark

Data Warehouses

Job description

Implement data pipelines integrating structured, semi-structured, and unstructured data for Predictive, AI, and Agentic solutions
Build and maintain scalable, robust ML- and AI-driven systems using Snowflake, REST APIs, AWS, or GCP infrastructure
Collaborate with Enterprise Data, IT, Cloud Enablement, and Enterprise Architecture teams and external partners
Translate business requests into technical requirements for small and medium-complexity engineering tasks
Validate internal and external data sources for availability and quality
Work with subject matter experts to describe and understand data lineage and suitability for use cases
Develop code enabling real-time modeling solutions to be ingested into front-end systems
Develop batch solutions implemented through modern scheduling and orchestration tools
Produce reproducible code artifacts and documentation using GitHub for handoff to other teams
Ensure reliability, availability, and scalability through monitoring, alerting, and incident management
Collaborate with AI Ops and infrastructure teams on deployment, operation, and maintenance of AI/ML systems

Requirements

Must be authorized to work in the U.S. now and in the future
Bachelor’s degree in Computer Science, Engineering, IT, Management Information Systems, or a related discipline
Experience developing solutions using Python and SQL
Experience using AI code assistants as part of daily workflow
Familiarity working with GitHub
Familiarity working in an Agile team, creating user stories, and planning/managing work over extended periods of time
Exposure to data ingestion from relational databases, Hadoop/Spark, cloud data sources, XML, JSON, CSV, or Parquet
Exposure to ETL concepts, metadata management, and data validation
Exposure to automation tools such as Autosys, Cron, or Airflow
Exposure to GCP or AWS services is a plus
Exposure to CloudFormation, Terraform, TeamCity, Jenkins, Octopus, and other IaC tools and platforms is a plus
Exposure to cloud data warehouses, automation, and data pipelines such as Snowflake, Redshift, or BigQuery is a plus
Able to communicate effectively with technical and non-technical teams
Able to translate complex technical topics into business solutions and strategies
Must be authorized to work in the US without company sponsorship
The company will not support the STEM OPT I-983 Training Plan endorsement for this position

Core Competencies

Demonstrates expertise in developing scalable ML and AI-driven systems using Python, SQL, and cloud platforms like AWS and GCP. Proficient in data pipeline implementation, data validation, and collaboration with cross-functional teams to translate business needs into technical solutions.

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