Copy of Senior Software Engineer, Data Acquisition

People Data Labs; Polska; Hybride; PLN 622 000 - 777 000; Plein temps

Avantages offerts par ce poste

Stock

Competitive salaries

Unlimited paid time off

Medical, dental, & vision insurance

Health, fitness, and stipends

Remote-friendly and flexible work

Résumé du poste

People Data Labs seeks a senior backend/data engineer to advance our data acquisition and processing platform. You will work on web crawling, large-scale distributed systems, and data pipelines to deliver high-quality data across datasets.

The role emphasizes autonomy in a remote-first, international environment with opportunities to contribute to new data products and scalable ingestion systems.

Qualifications

• 7+ years building backend or data-centric systems at scale.
• Strong Python/Go/Rust experience and async/concurrency knowledge.
• Solid understanding of distributed systems and fault tolerance.
• Experience with data ingestion, ETL, and data pipelines.
• Proficient with Linux/Unix and cloud basics.

Responsabilités

• Contribute to architecture and improve data acquisition platforms for reliability and throughput.
• Develop web crawling and data capture processes at scale.
• Build and operate large distributed systems delivering data across the web.
• Design backend services for data pipelines and task orchestration.
• Model and ensure quality, consistency, and lineage of captured data.
• Improve ingestion speed, scalability, and fault tolerance.
• Collaborate with product/engineering to craft data products and enhancements.
• Learn domain knowledge with mentorship and evolving systems.

Connaissances

Backend data engineering

Python

Go

Rust

Async programming

Distributed systems

Linux/Unix

Kubernetes

Data ingestion pipelines

Data modeling

Observability

Cloud fundamentals

Formation

Bachelor's degree in CS/Math/Engineering

Outils

Kafka

SQS

Airflow

Apache Spark

Databricks

SQL

Snowflake

BigQuery

Description du poste

linkNote 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 & Acquisition Team ensures our customers have standardized and high quality data to build upon.

You will be crucial in accelerating our efforts to build standalone data products that enable data teams and independent developers to create innovative solutions at massive scale. In this role, you will be working with a team to continuously improve our existing datasets as well as pursuing new ones.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

• Contribute to the architecture and improvement of our data acquisition and processing platform, increasing reliability, throughput, and observability
• Use and develop web crawling technologies to capture and catalog data on the internet
• Build, operate, and evolve large-scale distributed systems that collect, process, and deliver data from across the web
• Design and develop backend services that manage distributed job orchestration, data pipelines, and large-scale asynchronous workloads
• Structure and model captured data, ensuring high quality and consistency across datasets
• Continuously improve the speed, scalability, and fault-tolerance of our ingestion systems
• Partner with data product and engineering teams to design and implement new data products powered by the data you help collect, and enhance and improve upon existing products
• Learn and apply domain-specific knowledge in web crawling and data acquisition, with mentorship from experienced teammates and access to existing systems

The Technical Chops You’ll Need

• 7+ years of professional experience building or operating backend or infrastructure systems at scale
• Solid programming experience in Python, Go, Rust, or similar, including experience with async / await, coroutines, or concurrency frameworks
• Strong grasp of software architecture and backend fundamentals; you can reason clearly about concurrency, scalability, and fault tolerance
• Solid understanding of browser rendering pipeline, web application architecture (auth, cookies, http request / response)
• Familiarity with network architecture and debugging (HTTP, DNS, proxies, packet capture and analysis)
• Solid understanding of distributed systems concepts: parallelism, asynchronous programming, backpressure, and message-driven design
• Experience designing or maintaining resilient data ingestion, API integration, or ETL systems
• Proficiency with Linux / Unix command-line tools and system resource management
• Familiarity with message queues, orchestration, and distributed task systems (Kafka, SQS, Airflow, etc.)
• Experience evaluating and monitoring data quality, ensuring consistency, completeness, and reliability across releases

People Thrive Here Who Can

• Work independently in a fast-paced, remote-first environment, proactively unblocking themselves and collaborating asynchronously
• Communicate clearly and thoughtfully in writing (Slack, docs, design proposals)
• Write and maintain technical design documents, including pipeline design, schema design, and data flow diagrams
• Scope and break down complex projects into deliverable milestones, and communicate progress, risks, and blockers effectively
• Balance pragmatism with craftsmanship, shipping reliable systems while continuously improving them

Some Nice To Haves

• Degree in a quantitative field such as computer science, mathematics, or engineering
• Experience as a Red Teamer
• Experience working on large-scale data ingestion, crawling, or indexing systems
• Experience with Apache Spark, Databricks, or other distributed data platforms
• Experience with streaming data systems (Kafka, Pub/Sub, Spark Streaming, etc.)
• Proficiency with SQL and data warehousing (Snowflake, Redshift, BigQuery, or similar)
• Experience with cloud platforms (AWS preferred, GCP or Azure also great)
• Understanding of modern data storage and design patterns (parquet, Delta Lake, partitioning, incremental updates)
• Knowledge of modern data design and storage patterns (e.g., incremental updating, partitioning and segmentation, rebuilds and backfills)
• Experience building and maintaining data pipelines on modern big-data or cloud platforms (Databricks, Spark, or equivalent)

Our Benefits

• Stock
• Competitive Salaries
• Unlimited paid time off
• Medical, dental, & vision insurance
• Health, fitness, and office stipends
• The permanent ability to work wherever and however you want

Comp: $160K - $200K

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.

Qualified Applicants with arrest or conviction records will be considered for Employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

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