Senior Data Engineer Remote, USA

People Data Labs; Snowflake (AZ); Remote; USD 190,000 - 220,000; Full time

Job summary

Join a forward-thinking company as a Data Engineer, where you'll build cutting-edge data processing systems and contribute to innovative data solutions. This role offers the chance to work with a collaborative team focused on solving complex data challenges while enjoying a high degree of autonomy. Embrace the opportunity to design scalable data infrastructures and tackle undefined problems, all while fostering a culture of learning from failures. With competitive compensation and perks such as unlimited paid time off and flexible work arrangements, this position is perfect for those looking to make a significant impact in the data-as-a-service landscape.

Benefits

Unlimited paid time off

Health stipends

Fitness stipends

Stock options

Work from anywhere

Qualifications

• 5-7+ years of experience in data engineering with strong problem-solving skills.
• Expertise in Python, SQL, and Apache Spark for building scalable systems.

Responsibilities

• Build infrastructure for data ingestion, transformation, and loading.
• Develop CI/CD pipelines and anomaly detection systems for data quality.

Skills

Python

Apache Spark

SQL

Data Processing Systems

Data Pipeline Orchestration

Cloud Computing Services

Data Warehousing

Data Quality Evaluation

Education

Degree in Computer Science

Degree in Mathematics

Degree in Engineering

Tools

Databricks

AWS

Airflow

Kafka

Job description

Note for all engineering roles: with the rise of fake applicants and AI-enabled candidate fraud, we have built in additional measures throughout the process to identify such candidates and remove them.

About Us

People Data Labs (PDL) is the provider of people and company data. We do the heavy lifting of data collection and standardization so our customers can focus on building and scaling innovative, compliant data solutions. Our sole focus is on building the best data available by integrating thousands of compliantly sourced datasets into a single, developer-friendly source of truth. Leading companies across the world use PDL’s workforce data to enrich recruiting platforms, power AI models, create custom audiences, and more.

We are looking for individuals who can balance extreme ownership with a “one-team, one-dream” mindset. Our customers are trying to solve complex problems, and we only help them achieve their goals as a team. Our Data Engineering Team is the secret sauce behind all that we do and we are looking for the best of the best.

If you are looking to be part of a team discovering the next frontier of data-as-a-service (DaaS) with a high level of autonomy and opportunity for direct contributions, this might be the role for you. We like our engineers to be thoughtful, quirky, and willing to fearlessly try new things. Failure is embraced at PDL as long as we continue to learn and grow from it.

What You Get to Do

• Build infrastructure for ingestion, transformation, and loading an exponentially increasing volume of data from a variety of sources using Spark, SQL, AWS, and Databricks.
• Build an organic entity resolution framework capable of correctly merging hundreds of billions of individual entities into a number of clean, consumable datasets.
• Develop CI/CD pipelines and anomaly detection systems capable of continuously improving the quality of data we're pushing into production.
• Dream up solutions to largely undefined data engineering and data science problems.

The Technical Chops You’ll Need

• 5-7+ years of industry experience with clear examples of strategic technical problem-solving and implementation.
• Experience with Python.
• Expertise with Apache Spark (Java, Scala, and/or Python-based).
• Experience with SQL.
• Experience building scalable data processing systems (e.g., cleaning, transformation) from the ground up.
• Experience using developer-oriented data pipeline and workflow orchestration (e.g., Airflow (preferred), dbt, dagster or similar).
• Knowledge of modern data design and storage patterns (e.g., incremental updating, partitioning and segmentation, rebuilds and backfills).
• Experience working in Databricks (including delta live tables, data lakehouse patterns, etc.).
• Experience with cloud computing services (AWS (preferred), GCP, Azure or similar).
• Experience with data warehousing (e.g., Databricks, Snowflake, Redshift, BigQuery, or similar).
• Understanding of modern data storage formats and tools (e.g., parquet, ORC, Avro, Delta Lake).

People Thrive Here Who Can

• Balance high ownership and autonomy with a strong ability to collaborate.
• Work effectively remotely (able to be proactive about managing blockers, proactive on reaching out and asking questions, and participating in team activities).
• Demonstrate strong written communication skills on Slack/Chat and in documents.
• Scope and breakdown projects, communicate and collaborate progress and blockers effectively with your manager, team, and stakeholders.

Some Nice To Haves

• Degree in a quantitative discipline such as computer science, mathematics, statistics, or engineering.
• Experience working with entity data (entity resolution / record linkage).
• Experience working with data acquisition / data integration.
• Expertise with Python and the Python data stack (e.g., numpy, pandas).
• Experience with streaming platforms (e.g., Kafka).
• Experience evaluating data quality and maintaining consistently high data standards across new feature releases (e.g., consistency, accuracy, validity, completeness).
• Stock.
• Unlimited paid time off.
• Health, fitness, and office stipends.
• The permanent ability to work wherever and however you want.

Comp: $190K - $220K

People Data Labs does not discriminate on the basis of race, sex, color, religion, age, national origin, marital status, disability, veteran status, genetic information, sexual orientation, gender identity or any other reason prohibited by law in provision of employment opportunities and benefits.