Senior Data Platform Engineer

Black Dog Labs Limited; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Remote contract engagement

12+ months duration

Flexible schedule with overlap across时

Opportunity for production ownership

Job summary

Black Dog Labs is seeking a Senior Data Engineer to build and operate production-grade data platforms spanning ingestion, transformation, orchestration, storage-facing services, and APIs. The role blends hands-on data engineering with automation, observability, security, and reliability practices to ensure resilient pipelines.

Responsibilities include designing pipelines, data models, and API contracts; provisioning cloud resources with Terraform; and enabling CI/CD.

Qualifications

• 7+ years in data engineering, backend engineering, or DevOps.
• Strong SQL and data modeling fundamentals.
• Experience with Terraform and cloud platforms.

Responsibilities

• Design and operate batch and change-driven pipelines with orchestration and retries.
• Build tested transformations and data models; optimize SQL performance.
• Develop or support APIs with contracts, authentication, and auditability.
• Provision cloud resources with Terraform; automate delivery via CI/CD.
• Instrument services with logs, metrics, traces; define alerts and runbooks.
• Apply least-privilege access, secrets management, and data-quality checks.

Skills

SQL

Python

Bash/PowerShell

Documentation

Communication

Tools

Terraform

Azure

AWS

CI/CD

Git

Job description

Data Engineer India or Latin America preferred

Job details

India or Latin America preferred Eligibility

Senior Experience

Not specified Employment

About this role

Role overviewBuild and operate production-grade data platforms spanning ingestion, transformation, orchestration, storage-facing services, and APIs. The role combines hands-on data engineering with infrastructure automation, observability, security, and reliability practices. You will help make pipelines resilient, testable, and useful to product, engineering, and analytics teams.

Responsibilities

• Design and operate batch and change-driven pipelines, including scheduling, orchestration, schema evolution, retries, and failure recovery.
• Build tested transformation and merge processes, create consumable data models, and improve SQL performance.
• Develop or support APIs with well-defined contracts, authentication, validation, idempotency, and auditability.
• Provision and manage cloud resources with Terraform, automate delivery through CI/CD, and write shell scripts for operational tasks.
• Instrument services and pipelines with logs, metrics, and traces; define alerts, runbooks, and service-level objectives.
• Apply least-privilege access, secrets management, encryption, automated tests, and data-quality checks across the platform.

Requirements

• At least seven years of experience in data engineering, backend engineering, or DevOps.
• Strong SQL skills, including tuning, indexing, query plans, and relational database fundamentals.
• Proficiency with Python for data or service development and with Bash or PowerShell scripting.
• Experience with Terraform, infrastructure as code, CI/CD, and production operations.
• Strong Azure experience preferred; substantial AWS experience is also acceptable.
• Clear written and verbal communication, including the ability to document data contracts, mappings, runbooks, and technical decisions.

Nice to have

• Awareness of data protection or public-sector compliance requirements.
• Experience with dimensional modeling, BI consumption patterns, streaming or message queues, Parquet, monitoring platforms, or data governance.
• Exposure to simple operational interfaces or broader data-platform architecture.
• Effective, judicious use of AI coding tools alongside independent coding and testing.

Benefits and work setup

• Remote contract engagement, with preference for candidates in India or Latin America.
• Expected duration of at least 12 months, with possible extension or transition to full-time work.
• Flexible schedule with agreed overlap and on-call windows across time zones.
• Opportunity for production ownership and hands-on work with cloud, Terraform, orchestration, and modern data-platform tooling.