Principal Data Analytics Engineer

DriveWealth•New York, NY

5d•$200,000 - $250,000•Hybrid

About The Position

The Data & Analytics team is dedicated to building innovative data products that provide actionable insights, empowering our partners to succeed. We focus on curating and maintaining key data sources and statistics that serve both internal and external stakeholders.

Requirements

6-12+ years of hands-on experience in data engineering or analytics engineering.
Expert SQL: You don't just write queries; you understand execution plans, partition pruning, and how to optimize for compute-heavy environments.
Advanced dbt: Deep experience with dbt internals, custom materializations, macros, and package management.
Strong Python: Proficiency in Python for data manipulation (Pandas/Polars) and interaction with APIs/AWS services (boto3).
Experience architecting data models for complex financial instruments, ledgers, or high-frequency transaction data.
Experience building business metrics. ensure metric definitions are version-controlled, reusable, and mathematically consistent across all downstream reports.
You build solutions that are reusable and modular, not one-off scripts.
Experience treating data as software (Unit testing, CI/CD, Documentation, SLA monitoring).
Ability to independently diagnose cryptic error messages in distributed systems (Spark/Databricks/Snowflake) and resolve them.

Nice To Haves

Experience with Apache Spark or Databricks for heavy compute workloads.
Experience implementing Airflow or similar orchestrators.
Experience with Sigma Computing (from a data modeling perspective).
Experience using AI/LLM tools to enable faster, smarter analytics workflows

Responsibilities

Design and code complex dbt models and data transformation logic for high-volume financial datasets (trade transactions, order books).
Write production-grade Python scripts for advanced data processing, anomaly detection, and custom orchestration logic that SQL cannot handle alone.
Refactor legacy code and optimize incremental loading strategies to reduce costs and latency at scale.
Own the technical implementation of our data deployment reporting pipelines (Git, dbt Cloud), ensuring robust version control and seamless integration
Engineer automated testing frameworks and validation suites (using dbt tests/Python) to catch data issues before they reach the business layer
Provide Code reviews for Junior and senior developers code
Act as the "go-to" technical resource for Senior and Junior engineers when they hit blockers, helping them solve code-level problems through pair programming and guidance
Work across technical and business groups to problem-solve, consulting on impacts of future engineering changes to modeling outputs

Benefits

Competitive medical, dental, and vision insurance options
Mental health resources
Generous paid time off with observed holidays (varies per country)
Paid parental leave for biological and adoptive parents
Up to $2,500 or local equivalent each year to invest in continued education and personal development
Up to $900 each year or local equivalent for fitness and wellness reimbursement
Company-provided phone (varies by country)
For HQ in-office employees, a daily lunch stipend, unlimited snacks, and engaging office space in the Financial District
Pre-tax commuter benefits (US only)
Employer 401K match (US only)