Software Engineer/ Backend

We’re engaging a senior contract engineer to help deliver on high-impact, time-bound initiatives - including migrations to new data methodologies, deterministic identity matching using unique IDs, and new partner optimization feeds. You’ll own meaningful pieces of the stack end to end: from Spark pipelines and our data lake through workflow orchestration, partner integrations, and the APIs and delivery mechanisms that deliver signal to partners. This is a hands-on delivery role for someone who can ramp quickly and produce production-quality work with minimal onboarding., * Build, optimize, and operate production Apache Spark pipelines that generate attributed conversion and optimization feeds from large-scale impression and conversion data.

• Design and evolve data processing and models across modern data lake and warehouse technologies, orchestrated with a production workflow scheduler on AWS.

• Build and operate partner optimization feeds and integrations with external partners, including schemas, identity fields and unique IDs, file delivery, reconciliation, and SLAs.

• Build, change, and operate production REST APIs, including PHP APIs, delivering secure, backward-compatible changes end to end (implementation, validation, authorization, data access, documentation, automated testing, and production diagnostics).

• Trace and modify behavior across controllers, database queries, templates, JavaScript, and automated tests.

• Diagnose production failures, reconcile partner-facing data, execute backfills, and manage staged releases and rollbacks.

• Write and maintain unit and integration tests across pipelines, APIs, and feeds.

• 7+ years of professional software or data engineering experience.

• 4+ years building, optimizing, and maintaining production Apache Spark pipelines, with strong Java and Python skills across JVM Spark and PySpark.

• Advanced SQL, relational data modeling, and large-scale data processing experience, including production work with Snowflake, MySQL, and Iceberg.

• 3+ years operating AWS data workloads using S3 and Airflow (or equivalent production workflow orchestration); container orchestration and data-catalog experience a plus.

• 3+ years building, changing, and operating production REST APIs, including PHP APIs built with Symfony or a closely equivalent PHP MVC framework.

• Demonstrated proficiency using AI development tools to deliver production-quality work efficiently - including AI-assisted coding, code review, documentation, and investigation, working with agentic code harnesses, and spec-based (spec-driven) AI development - with the judgment to know when to rely on AI output and when not to.

• Ability to independently deliver secure, backward-compatible API changes, including implementation, validation, authorization, data access, documentation, automated testing, and production diagnostics.

• Experience implementing external provider or client integrations involving schemas, APIs, file delivery, identity fields, reconciliation, privacy-sensitive data, and SLAs.

• Production full-stack experience with PHP, Symfony (or a comparable framework), Doctrine, Twig (or another server-rendered template system), and JavaScript.

• Ability to trace and modify behavior across controllers, database queries, templates, JavaScript, and automated tests.

• Experience writing unit and integration tests for data pipelines, APIs, and web applications.

• Ability to diagnose production failures, reconcile data, execute backfills, manage staged releases and rollbacks, and support delivery commitments.

• Hands-on experience building and running big data systems, with a focus on performance, reliability, and data quality.

• Experience in ad tech or advertising measurement, such as attribution, conversions, audience and impression data, identity matching, or partner optimization feeds.

• Ability to ramp quickly and deliver with minimal onboarding in an existing, complex codebase.

Preferred Skills:

• Direct experience building partner optimization or advertising feeds with external platforms (DSPs, publishers, or measurement partners).

• Experience with deterministic and probabilistic identity matching - unique IDs, device IDs, IP-based matching, and identity graphs.

• Familiarity with edge/log delivery infrastructure and pixel/impression tracking.

• Experience with data lake table formats and query engines at large scale.

• Experience with privacy and compliance-driven data workflows (deletion, opt-out, suppression, data retention).

• Comfort operating in uncharted territory - turning ambiguity into production systems without a detailed guide.