Data Engineer

The Doyle Group; Bridgeport (CT); On-site; USD 120,000 - 170,000; Full time

Benefits offered by this job

Fully remote

Job summary

The Doyle Group presents a Data Engineer opportunity for someone who enjoys building robust data pipelines and owning end-to-end data flows. The role is fully remote and focuses on designing scalable pipelines, ETL/ELT processes, and data integrations across ad platforms, CRMs, and internal analytics tools.

You will work on a stack aligned with senior engineers, partnering with analysts and development teams to enable analytics and AI-ready workflows.

Qualifications

• 3+ years in data engineering or backend data work.
• Strong Python, clean modular code and API experience.
• Advanced SQL in Snowflake or similar cloud warehouse.
• AWS hands-on experience and IaC (Terraform/CloudFormation).
• Experience with ELT/ETL tools like Airbyte or Funnel.io.

Responsibilities

• Design, build, and maintain scalable data pipelines from ingestion to analytics tables.
• Own ETL/ELT lifecycle including extraction, transformation, loading, orchestration, retries and backfills.
• Integrate external systems via REST APIs with OAuth 2.0 and schema drift handling.
• Configure ELT connectors and manage schedule, schema changes, and backfills.
• Support AWS infrastructure as code and contribute to Snowflake schema design and performance.
• Build data quality checks and observability for freshness, volume, and validation.
• Collaborate with analytics, media buying, and finance teams; review code and mentor teammates.

Skills

Python development

SQL expertise

REST API development

Clear communication

Analytical mindset

Education

Bachelor's in CS/Engineering/Math/Statistics or equivalent

Tools

Snowflake

Airbyte

Funnel.io

Terraform

CloudFormation

AWS services (S3, Lambda, IAM)

Temporal

Prefect

Job description

• Contract to Hire, fully remote - candidates must be authorized to work in the U.S. without current or future sponsorship.

ABOUT THE DOYLE GROUP

The Doyle Group is a proven partner for Placement and Consulting services, headquartered in Denver, CO. With over 30 years of industry experience, our consultative approach helps clients secure top IT talent that fits seamlessly into their team and culture.

POSITION SUMMARY

Our client is hiring a Data Engineer to build and maintain the pipelines, connectors, and integrations that power reporting, analytics, and AI-driven workflows across the business. The role is roughly 70% hands‑on pipeline/platform engineering and 30% partnership with analysts, media buying, and development teams.

This is an individual-contributor role with real ownership from day one, working on the same stack as the team's senior engineers. No leadership expectation required — strong fundamentals and the right mindset matter more.

RESPONSIBILITIES

• Design, build, and maintain scalable, idempotent data pipelines from raw ingestion through analysis-ready tables
• Own pieces of the ETL/ELT lifecycle: extraction, transformation, loading into Snowflake, orchestration, scheduling, retries, alerting, backfills
• Integrate external systems via REST APIs (ad platforms, CRMs, call tracking, vendor feeds), handling OAuth 2.0, pagination, rate limits, schema drift, and partial failures
• Configure and manage ELT connectors like Airbyte and Funnel.io, including sync scheduling and schema-change handling
• Support AWS infrastructure as code (Terraform or CloudFormation)
• Contribute to Snowflake schema design, dimensional modeling, partitioning/clustering, warehouse sizing, and query performance tuning
• Build data quality and observability checks: freshness/volume checks, row‑level validation, reconciliation, alerting
• Help monitor and optimize platform cost (Snowflake credits, AWS spend) as part of the design process
• Partner with analytics, media buying, account, and finance teams on data needs and issue resolution
• Collaborate with developers on code review, paired programming, bug fixes, and engineering standards
• Contribute to AI/agent‑ready processes, exposing data sources as reliable, self‑service tools for internal AI workflows
• Support hiring, onboarding, and mentoring as the team grows

MINIMUM EXPERIENCE

• 3+ years in data engineering, analytics engineering, or backend data‑focused work
• Strong production Python: clean/modular/testable code, dependency management, error handling and logging, building/consuming REST APIs (FastAPI, Flask, or similar), working within frameworks like Django or writing custom connectors
• Advanced SQL (CTEs, window functions, query optimization) in Snowflake or a comparable cloud warehouse
• Hands‑on AWS: core comfort with S3, Lambda, IAM; familiarity with several of Glue, Step Functions, EventBridge, ECS/Fargate, Secrets Manager, CloudWatch, RDS, SQS/SNS
• Infrastructure as code experience (Terraform or CloudFormation), including state, modules, and multi‑environment management
• Experience with a managed ELT/ETL platform such as Airbyte or Funnel.io
• Pipeline orchestration experience with Temporal, Prefect, or AWS Step Functions
• Solid database fundamentals: normalization, indexing, transactions, constraints, data modeling trade-offs
• Comfortable working with unstructured, messy, inconsistent datasets
• Clear communication with non-technical stakeholders; strong attention to detail and organizational skills
• Bachelor's in CS, Engineering, Math, Statistics, or related field, or equivalent hands‑on experience
• Must be legally authorized to work in the U.S. without sponsorship now or in the future

ADDITIONAL PLUS

• Background in media, advertising, direct-response marketing, or an adjacent domain (CRM, sales enablement, DSP/media platform)
• Hands‑on exposure to LLMs or AI agents, even informal/productivity‑focused use
• Experience across a high‑volume connector environment (dozens of integrations)
• Comfort in a fast‑paced, deliverable‑driven, daily‑standup team culture
• Genuine interest in growing toward more senior or technical‑lead scope over time