Capgemini · Atlanta, GA

Salary
$62,000–$72,000from the description
Posted
Jul 13, 2026
Location
Atlanta, GA
Last confirmed open
Jul 21, 2026

What this job asks for AI summary

This role sits within a large bank's Chief Data Office, focused on building a greenfield enterprise data pipeline platform from the ground up. The engineer will design and develop integrations with Spark Engine and Spark Flow, build and consume RESTful APIs, and work with distributed compute frameworks to handle high-volume data. It suits someone with solid Apache Spark experience and a background in distributed systems and API development.

Mid level · Atlanta-Sandy Springs-Alpharetta, GA · Full-time

Must have (5)
Apache SparkREST APIsPythonSpark Flowmicroservices
Nice to have (9)
HadoopHiveSQLKafkaAWS, Azure or GCPDockerKubernetesGitHub ActionsCI/CD

“or” means any one of them counts — you don't need all of them.

We read this from the posting text with AI. Skim the description below before ruling yourself out.

How this req sits in the market our data

Roughly 180 people in the Atlanta-Sandy Springs-Alpharetta, GA area plausibly meet what this posting asks for (database architects). range 95–230

Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.

What won't set you apart
Python55%

Most people in this occupation already list these. Still required — just not what gets you shortlisted.

What the occupation pays Median $142,568 (middle half $134,044–$177,990). This posting is about at that midpoint.

Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.

Why we read it this way (6)

The job title in the posting is 'Spark Engineer' / 'System Engineer (US L4)' with no explicit seniority level word in the public-facing title, hence advertised seniority is Unspecified. The internal Capgemini level 'L4' typically maps to a mid-level individual contributor.

The compensation range of $62,000–$72,000/year is notably low for a senior data/platform engineer role, which further supports a Mid-level classification rather than Senior.

SOC classification is a genuine toss-up: the role centers on building enterprise data pipeline infrastructure (ETL, Spark, distributed compute) which points to 15-1243 (Database Architects / Data Engineers), but the emphasis on API integrations, microservices, and greenfield platform development also fits 15-1252 (Software Developers). 15-1243 was chosen as primary because the core deliverable is a unified data pipeline execution platform.

Apache Spark, Spark Flow, REST APIs, Python, and microservices are listed under the 'Qualifications' / 'Key Responsibilities' sections with firm language and are treated as hard gates. Big data ecosystem tools (Hadoop, Hive, SQL, Kafka) and cloud platforms are framed as 'Familiarity with' and 'Exposure to', making them preferred.

Docker/Kubernetes and GitHub Actions/CI/CD appear only in the team overview narrative ('The project team is building…') rather than in the formal qualifications block, so they are treated as preferred/stack context.

The posting lists Atlanta, GA as the location, though the role description references Charlotte, US — Atlanta is used as it is the stated posting location.

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