Data Engineer

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Neurons Lab

WebsiteLinkedInAll Job Openings

51 - 200 employees

💰 Corporate Round on 2022-10

Neurons Lab is a globally distributed AI R&D company that helps deep tech innovators to accelerate data-driven products development and launch. Our team has expertise in fundamental sciences, full-stack AI/ML engineering, and product design. Such a rare combination and access to scarce talent allows Neurons Lab to build disruptive solutions for clients in HealthTech and EnergyTech industries. Neurons Lab operates within a proprietary delivery framework that is tailored to the innovation environment: fierce competition, tight timelines, little-to-none datasets, and the necessity to generate novel solutions.

📋 Description

• Reproduce a descriptive-statistics report end-to-end so any figure traces back to raw source — closing the gap the client admitted (numbers they can't currently defend). • Profile and reconcile differing source schemas across acquired entities: map differing field names, types, encodings and business definitions for the same concept into one conformed model. • Build dbt staging → intermediate → mart models with tests; codify the harmonized definitions the Data Science Lead specifies. • Write Great Expectations suites (null / range / uniqueness / referential checks) and wire them into the pipeline so bad data fails loudly rather than silently corrupting analysis. • Implement entity / identity resolution (deterministic + fuzzy matching) where there is no clean shared key for the same customer or account across sources. • Implement and verify anonymization / pseudonymization (hashing / tokenization / k-anonymity) and evidence that re-identification risk is controlled for the client's IT / compliance team. • Optimize Spark / Glue jobs over tens of millions of rows — partitioning, file formats (Parquet), incremental loads, cost control. • Orchestrate with Airflow / Step Functions; build repeatable, scheduled pipelines rather than one-off scripts. • Prepare clean, documented, feature-ready datasets for the PD / delinquency models. • Document runbooks so the offshore team can operate the pipelines and handover takes days, not weeks; help scope onboarding of the remaining (Ireland + additional) sources.

🎯 Requirements

• 4+ years in data engineering, with strong AWS + Spark / SQL at scale • Demonstrated experience harmonizing / integrating data across multiple source systems • Experience building validated, reproducible pipelines in a regulated environment (BFSI, healthcare, government) — strong plus • Comfortable stepping into a messy, partly-built data estate and bringing it up to standard • Comfortable as the sole or lead data engineer on a small (3–4 person) delivery pod

🏖️ Benefits

• Full-time engagement preferable.