Sr. Data Engineer

Albano Systems, Inc.; New York (NY); On-site; USD 140,000 - 200,000; Full time

Job summary

Albano Systems, Inc. seeks a senior data engineer/architect to partner with Cybersecurity leaders and build scalable analytics products. You will ingest and model security data, develop executive dashboards, and drive data‑driven risk insights for governance and frontline teams.

Ideal candidates have 8+ years in data engineering, strong Python/SQL skills, and experience with Databricks, Redshift, Snowflake or Alteryx, plus leadership capabilities for cross‑functional work.

Qualifications

• Bachelor's degree in a relevant field.
• 8+ years of data engineering/analytics/architecture experience.
• Experience designing data pipelines, models, and analytics architectures (batch/streaming).
• Experience with Databricks, Redshift, Snowflake, Alteryx or equivalent.
• Strong coding in Python and SQL; ability to evaluate data sources.
• Experience partnering with data engineering, platform, and architecture teams.

Responsibilities

• Partner with Cybersecurity leaders to define data‑driven use cases aligned to risk priorities.
• Ingest, transform, model security and IT data ensuring quality and lineage.
• Develop executive dashboards and strategic metrics for leadership and governance.
• Prototype integrations across Cyber tools and enterprise data platforms.
• Apply advanced analytics and AI‑augmented analysis to translate telemetry into risk indicators.
• Translate complex findings into clear narratives for executives and non‑technical stakeholders.

Skills

8+ years data engineering/analytics/AI

Data pipelines

Data modeling

Analytics architectures

Python

SQL

Collaboration with data teams

AI analytics tools

Technical leadership

Tableau

Power BI

Data lakes/warehouses

Communication

Education

Bachelor's degree in a relevant field

Tools

Databricks

Redshift

Snowflake

Alteryx

Job description

W2 ONLY - NO CORP TO CORP - NO 3RD PARTY CANDIDATES - NO VISA SPONSOR/TRANSFER

CAN WORK IN NYC/BOSTON/SPRINGFIELD

Partner with Cybersecurity leaders, risk stakeholders, and non‑Cyber teams to define and deliver data‑driven Cyber use cases, aligned to enterprise risk priorities and frameworks (e.g., NIST CSF).

Leverage scalable data pipelines, models, and architectures that enable Cyber analytics, AI, reporting, and advanced use cases across vulnerability management, threat exposure, control effectiveness, and risk insights.

Work directly with data owners and platform teams to ingest, transform, normalize, and model security and IT datasets, ensuring data quality, lineage, and trust.

Develop and operationalize analytics products including executive dashboards, strategic metrics, and operational reporting for leadership, governance forums, and front‑line Cyber teams.

Prototype and productionize integrations across Cyber tools and enterprise data platforms, partnering closely with data engineering and architecture teams to ensure sustainability, performance, and supportability.

Apply advanced analytics, data modeling, and automation techniques to translate raw Cyber telemetry into actionable outcomes, risk indicators, and decision support.

Leverage AI‑assisted development and analytics workflows (e.g., Claude, code‑generation tools, AI‑augmented analysis) to accelerate engineering, insight generation, and experimentation—while operating within established security and data governance controls.

Translate complex technical findings into clear, consumable narratives for executive and non‑technical stakeholders, connecting analytics outputs directly to Cyber risk, business impact, and outcomes.

Serve as a thought partner and technical advisor, helping shape the Cyber data strategy, architecture direction, and future‑state analytics capabilities.

Skills: Minimum Qualifications

• Bachelor's degree in a relevant field (e.g., Computer Science, Data Engineering, Analytics, Information Security, or equivalent experience).
• 8+ years of deep hands‑on experience in data engineering, analytics, or data architecture.
• Demonstrated experience designing and building data pipelines, data models, and analytics architectures, including batch and/or streaming patterns.
• Practical experience partnering with or working on modern data platforms and tools such as Databricks, Redshift, Snowflake, Alteryx, or equivalent technologies.
• Strong coding proficiency (e.g., Python, SQL) with the ability to assess multiple data sources and determine feasibility, data gaps, and engineering approaches to support Cyber use cases.
• Experience collaborating closely with data engineering, platform, and architecture teams to ensure long‑term operability and support.

Preferred Qualifications

• Experience incorporating or experimenting with AI‑enabled analytics or development tools (e.g., Claude, AI code assistants, agent‑based analytics) in a secure enterprise environment.
• Leadership experience as a technical lead, architect, or people manager within data, analytics, or Cyber practices.
• Strong proficiency with data visualization and BI tools (e.g., Tableau, Power BI) to deliver executive‑ready, actionable insights.
• Experience working with enterprise data ecosystems, including data lakes, warehouses, and shared analytics platforms.
• Exceptional communication skills with the ability to translate complex technical outputs into business and risk context for senior leaders and non‑technical audiences.