Full-Time

Senior Data Engineer

Rearc

Rearc

11-50 employees

Engineering services for GenAI, data, AWS

Compensation Overview

$160k - $200k/yr

New York, NY, USA

Hybrid

Category
Data & Analytics (1)
Required Skills
Dynamodb
Microsoft Azure
Redshift
Python
Airflow
NoSQL
BigQuery
Apache Spark
SQL
Postgres
Data Engineering
CloudFormation
AWS
Pandas
Terraform
NumPy
Databricks
Snowflake
Google Cloud Platform
Requirements
  • 8+ years of professional experience in data engineering across modern cloud architectures and diverse data systems.
  • Expertise in designing and implementing data warehouses and data lakes across modern cloud environments (e.g., AWS, Azure, or GCP), with experience in technologies such as Redshift, BigQuery, Snowflake, Delta Lake, or Iceberg.
  • Strong Python experience for data engineering, including libraries like Pandas, PySpark, NumPy, or Dask.
  • Hands-on experience with Spark and Databricks (highly desirable).
  • Experience building and orchestrating data pipelines using Airflow, Databricks, DBT, or AWS Glue.
  • Strong SQL skills and experience with both SQL and NoSQL databases (PostgreSQL, DynamoDB, Redshift, Delta Lake, Iceberg).
  • Solid understanding of data architecture principles, data modeling, and best practices for scalable data systems.
  • Experience with cloud provider services (AWS, Azure, or GCP) and comfort using command-line interfaces or SDKs as part of development workflows.
  • Familiarity with Infrastructure as Code tools such as Terraform, CloudFormation, ARM/Bicep, or AWS CDK.
  • Excellent communication skills, able to explain technical concepts to technical and non-technical stakeholders.
  • Adaptability and comfort working in dynamic, fast-changing environments.
Responsibilities
  • Provide strategic data engineering leadership by shaping the vision, roadmap, and technical direction of data initiatives to align with business goals.
  • Architect and build scalable, reliable data solutions, including complex data pipelines and distributed systems, using modern frameworks and technologies (e.g., Spark, Kafka, Kubernetes, Databricks, DBT).
  • Drive innovation by evaluating, proposing, and adopting new tools, patterns, and methodologies that improve data quality, performance, and efficiency.
  • Apply deep technical expertise in ETL/ELT design, data modeling, data warehousing, and workflow optimization to ensure robust, high-quality data systems.
  • Collaborate across teams—partner with engineering, product, analytics, and customer stakeholders to understand requirements and deliver impactful, scalable solutions.
  • Mentor and coach junior engineers, fostering growth, knowledge-sharing, and best practices within the data engineering team.
  • Contribute to thought leadership through knowledge-sharing, writing technical articles, speaking at meetups or conferences, or representing the team in industry conversations.

Rearc provides engineering-driven services to help enterprises accelerate GenAI, data platforms, and cloud development, with a focus on AWS as an Advanced Consulting Partner. Teams assess current data and AI goals and design and implement end-to-end AWS-based solutions, including data pipelines, GenAI tooling, MLOps, and security/compliance. It differentiates itself through deep engineering in the AWS ecosystem and a proven track record with regulated industries, offering bespoke, end-to-end services rather than off-the-shelf software. The goal is to enable enterprises to rapidly adopt scalable, secure GenAI and cloud platforms that drive measurable business outcomes while meeting regulatory constraints.

Company Size

11-50

Company Stage

N/A

Total Funding

N/A

Headquarters

New York City, New York

Founded

2016

Simplify Jobs

Simplify's Take

What believers are saying

  • Financial firms deploy proprietary LLMs, boosting MLOps demand to $15B by 2026.
  • Healthcare AI diagnostics scale under FDA 2024 guidance, needing compliance consulting.
  • Data mesh architectures standardize, requiring federated platform design services.

What critics are saying

  • AWS expands consulting, compressing Rearc margins within 6-12 months.
  • GenAI commoditization via Bedrock erodes bespoke premiums in 6-12 months.
  • Talent attrition to Accenture and Deloitte hits within 12-24 months.

What makes Rearc unique

  • Rearc specializes in bespoke LLM and MLOps for financial services enterprises.
  • Engineers from Wall Street Journal founding drive cloud-native expertise since 2016.
  • AWS Advanced Partner status enables specialized GenAI platform acceleration.

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Benefits

Health Insurance

401(k) Retirement Plan

401(k) Company Match

Paid Vacation

Parental Leave

Professional Development Budget

Remote Work Options