Senior Data Engineer

The Leading Hotels of the World

. Design, build, and optimize data pipelines for ingestion, transformation, and delivery .

Posted 9/28/2026full-timeNew York City • New York • United StatesSenior💰 $140,000 - $160,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and optimizing data pipelines, data architectures, and data products while ensuring data quality and governance. Proficient in leveraging modern data platforms and tools to support analytics and machine learning initiatives.

Highest-signal resume keywords

Data Pipeline DevelopmentData Architecture DesignAWS ProficiencyETL/ELT FrameworksSQL and Python Expertise

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentData ModelingData GovernanceData QualitySQLPythonETL ToolsData ProcessingData WarehousingData Lakes

Soft Skills

Strong CommunicationCollaborationMentoring

Tools & Technologies

SnowflakeBigQueryRedshiftDatabricksAWS GlueAmazon S3Amazon RedshiftAmazon Aurora MySQLSparkAirflow

Industry Keywords

Data EngineeringDataOpsData AnalyticsMachine LearningBusiness Operations

Tech Stack

Tools & technologies

AirflowAmazon RedshiftAWSBigQueryDistributed SystemsETLMySQLPythonSparkSQL

About the role

Key responsibilities & impact

Design, build, and optimize data pipelines for ingestion, transformation, and delivery
Develop and maintain scalable data architectures, including data lakes and data warehouses
Build reliable, reusable data products and data models supporting reporting, analytics, AI, machine learning, and business operations
Optimize performance across data platforms and pipelines
Ensure data is clean, reliable, accessible, and available for enterprise use
Apply data governance, quality, lineage, and security standards within data engineering solutions
Support delivery of trusted and consistent enterprise data
Partner cross-functionally with business and technology teams to deliver timely, high-quality data
Help define and implement DataOps and data engineering best practices
Mentor junior data engineers and promote data engineering best practices

Requirements

What you’ll need

Bachelor’s degree (BS) required
7+ years of experience in data engineering or related field
Deep experience with modern data platforms, including Snowflake, BigQuery, Redshift, and Databricks
Strong experience with AWS, including AWS Glue, Amazon S3, Amazon Redshift, and Amazon Aurora MySQL
Strong hands-on experience with ETL/ELT tools and frameworks, including Spark, Airflow, and dbt
Advanced proficiency in SQL and Python
Experience designing and building scalable data pipelines, data models, and data products
Experience with large-scale data processing and distributed systems
Knowledge of data quality, lineage, performance tuning, security, and established data governance standards
Strong communication skills with the ability to work cross-functionally
Ability to demonstrate LHW’s performance drivers: Accountability, Adaptability, Collaboration, Curiosity, and Empathy

Benefits

Comp & perks

22 days of Paid Time Off (PTO)
11 paid holidays, including birthdays as a floating holiday
Medical coverage available within the first month
Health Savings Account (HSA) with Company contribution
401(k) company match up to 4% of salary
Up to $500 for home office setup credit
Up to $500 travel credit
Unlimited access to financial advisors
Collaborative and inclusive work environment