Job Title: Core Engineer
Number: 1721-1
Duration: 12 months with a possibility of further extension
Client Location: Jacksonville, FL
Onsite Position

About the Position :
Senior hands-on engineer to own a data and event backbone - how events flow, and how live and historical data are separated, stored, secured, and served. Accountable for delivering their scope, built correctly, securely, and on time. A hands-on expert engagement: building, not advising, requiring real streaming and data-modeling depth.
This is core software development and transaction-processing work - building the operational data backbone of a live system. It is not an analytics, data warehousing, or business intelligence role; the data modeling here is transactional (OLTP-style), not dimensional/reporting modeling.

Must-have summary - the hard bar
A candidate must clear all of these to be a fit:
• 6-8 years hands-on, currently building - recent, personally-built and delivered work they can speak to in depth.
• Streaming / event-processing depth - partitioning, ordering, consumer semantics, replay (not batch-ETL-only).
• Strong SQL and relational data modeling/projection design - the read layer is relational; SQL-light is not a fit.
• Object storage and Lakehouse depth, including its security posture - not just basic file-store usage.
• Streaming-to-object-store integration - moving the event log to archival storage with idempotent / exactly-once delivery.
• Data-plane security - tenant / row-level isolation, object-storage security (encryption, immutability, public-access blocking), and encryption in transit.
• Test judgment for data properties - event replay, projection-versus-log correctness, idempotency, cross-tenant isolation.
• AI-assisted-development fluency and verification - directs and verifies AI-generated code and tests, catching plausible-but-wrong output.
• Strong Python; serverless-first, container fluency, local cloud emulation.
• Ownership and delivery discipline; clear communication; can hold core consistency under direction when the lead is unavailable.

Core skills - full detail
• 6-8 years hands-on, with recent work you personally built and delivered.
• Depth in streaming / event-processing platforms - partitioning, ordering, consumer semantics, replay.
• Streaming-to-object-store integration - moving the event log into archival object/Lakehouse storage reliably, with idempotent / exactly-once delivery and schema handling.
• Strong relational database proficiency - the read/projection layer is relational and central to the role.
• Strong read-model / projection design and data modeling.
• Object storage and Lakehouse depth - bucket/prefix design, partitioning, schema evolution, snapshot/lifecycle management, and columnar query over it.
• Data-plane security across all three stores:
• Tenant/party data isolation - row / tenant-level isolation, enforced server-side and per request.
• Object-storage security - public-access blocking, bucket/prefix isolation, encryption with managed keys, immutability where retention requires it, and lifecycle/tiering.
• Encryption at rest and in transit across the relational store, the event log, and object/lakehouse storage.
• Sound data-lifecycle judgment - what to cache, project, or archive, and why; hot vs. cold separation.
• Security verification of AI-generated code - catches data-exposure and access-control flaws in generated output before they land.
• Testing the hard data-plane properties - event ordering/replay, projection-versus-log correctness, idempotency / exactly-once, and cross-tenant isolation (proving data can't leak).
• Test strategy and verification judgment - reviews generated tests for genuine coverage rather than green-but-hollow passing.
• Hands-on with automated testing frameworks - unit / integration testing, service mocking / stubbing, and test-data generation, alongside local cloud emulation.
• Ownership and delivery discipline - accountable for getting work done under time pressure.
• Clear communicator - surfaces risk and status clearly.
• Strong Python proficiency.
• Serverless-first cloud-native build - object storage and serverless compute as primary building blocks.
• Container fluency - containerized local development and container-image packaging of compute.
• Local cloud emulation for development and testing.
• Fluent with modern AI-assisted development tooling - directs and verifies AI-generated code with rigor.
• Comfortable applying an established architectural decision framework under direction - able to hold core consistency when the lead is unavailable.
Advantageous
• Cloud data services.
• Key management / secrets handling for data stores.
• Data retention / records-lifecycle and immutability experience.
• Container orchestration - good to know, not required.
• High-volume IoT / telemetry data.
• Observability / distributed-tracing tooling.
• Domain exposure in a data-intensive, operationally complex industry.

Assessment
A deep-dive on a data/event system you personally built
- including how you moved the event stream into archival storage, isolated tenants, secured object storage, and protected data at rest and in transit
- plus how you'd verify a data-layer implementation is correct and judge whether its test suite proves the hard properties (replay, projection correctness, isolation).

DataSoft Technologies, Inc. provides staff augmentation services for Information Technology and Automotive Services. Our team member benefits include:

• Paid Holidays/Paid Time Off (PTO)
• Medical/Dental Insurance
• Vision Insurance
• Short Term/Long Term Disability
• Life Insurance
• 401 (K)