AHEAD

AHEAD

AHEAD accelerates the impact of technology on clients by engineering customized data, developer, and infrastructure platforms that improve IT operations. By weaving together cloud infrastructure, intelligent operations, and modern applications, we help...

IT Services
1001-5000
$43M raised

Description

  • Build, maintain, and improve batch and incremental ingestion pipelines, including API pagination, rate limits, retries, schema changes, deletes, and backfills.
  • Develop SQL and Python solutions to collect, validate, transform, and publish data from enterprise systems and approved APIs.
  • Build Snowflake and dbt transformations, incremental models, and reusable datasets with history preservation and cross-system identifier reconciliation.
  • Implement data product standards for metadata, schemas, quality checks, lineage, and freshness monitoring.
  • Create automated unit, integration, and data-quality tests; investigate and resolve discrepancies before publishing data.
  • Implement and test least-privilege access controls, service identities, data classification, masking, and row- or column-level security.
  • Build version-controlled deployment and rollback processes for code, database changes, and access grants across environments.
  • Monitor pipeline health, freshness, performance, and failures; recover failed loads, troubleshoot root causes, and maintain runbooks.
  • Optimize Snowflake workloads, queries, transformations, and storage patterns for performance, reliability, and cost.
  • Partner with Analytics, application owners, Integration Platform, Security, and data consumers to deliver governed, maintainable data solutions.

Requirements

  • Bachelor’s degree in computer science, information systems, engineering, mathematics, or a related field, or equivalent experience.
  • 3+ years of experience in data engineering, software engineering, analytics engineering, or a related technical role.
  • Professional experience writing production-quality SQL and Python.
  • Experience independently building, deploying, and supporting production data pipelines, including orchestration, scheduling, dependency management, monitoring, and failed-run recovery.
  • Hands-on experience with a cloud data warehouse and transformation framework; Snowflake and dbt are strongly preferred.
  • Understanding of relational and dimensional data modeling, ELT/ETL patterns, APIs, source-system integration, schema evolution, and historical-change handling.
  • Experience with source control, code review, automated testing, and CI/CD.
  • Experience using AI-assisted development tools while critically reviewing generated code and tests.
  • Knowledge of data quality, metadata, lineage, role-based access, privacy, and secure handling of enterprise data and credentials.
  • Experience with Azure storage, containerized or serverless workloads, Terraform, Salesforce or NetSuite APIs, data observability, catalogs, or lineage tooling is preferred.

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