{"id":3304385,"url":"https://alion.io/job/people-data-labs-data-engineer","title":"Data Engineer","company":{"id":4933,"name":"People Data Labs","domain":"peopledatalabs.com","url":"https://alion.io/company/people-data-labs","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":180000,"max":220000,"currency":"USD","period":"year","gross":null,"usd_annual":220000},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Delta Lake","optional":false},{"name":"GCP","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Java","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Slack","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Apache Kafka","optional":true},{"name":"NumPy","optional":true}],"status":"live","first_seen_at":"2026-10-26T23:18:12Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-10-27T23:11:30Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"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.\nAbout Us\nPeople 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.\nWe 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.\nIf 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.\nWhat You Get to Do\nBuild infrastructure for ingestion, transformation, and loading an exponentially increasing volume of data from a variety of sources using Spark, SQL, AWS, and Databricks\n\nBuilding an organic entity resolution framework capable of correctly merging hundreds of billions of individual entities into a number of clean, consumable datasets.\n\nDeveloping CI/CD pipelines and anomaly detection systems capable of continuously improving the quality of data we're pushing into production.\n\nDreaming up solutions to largely undefined data engineering and data science problems.\n\nThe Technical Chops You’ll Need\n3-5+ years of industry experience with clear examples of strategic technical problem-solving and implementation\n\nStrong software development fundamentals.\n\nExperience with Python\n\nExpertise with Apache Spark (Java, Scala, and/or Python-based)\n\nExperience with SQL\n\nExperience building scalable data processing systems (e.g., cleaning, transformation) from the ground up.\n\nExperience using developer-oriented data pipeline and workflow orchestration (e.g., Airflow (preferred), dbt, dagster or similar)\n\nKnowledge of modern data design and storage patterns (e.g., incremental updating, partitioning and segmentation, rebuilds and backfills)\n\nExperience working in Databricks (including delta live tables, data lakehouse patterns, etc.)\n\nExperience with cloud computing services (AWS (preferred), GCP, Azure or similar)\n\nExperience with data warehousing (e.g., Databricks, Snowflake, Redshift, BigQuery, or similar)\n\nUnderstanding of modern data storage formats and tools (e.g., parquet, ORC, Avro, Delta Lake)\n\nPeople Thrive Here Who Can\nBalance high ownership and autonomy with a strong ability to collaborate\n\nWork effectively remotely (able to be proactive about managing blockers, proactive on reaching out and asking questions, and participating in team activities)\n\nDemonstrate strong written communication skills on Slack/Chat and in documents\n\nExhibt experience in writing data design docs (pipeline design, dataflow, schema design)\n\nScope and breakdown projects, communicate and collaborate progress and blockers effectively with your manager, team, and stakeholders\n\nSome Nice To Haves\nDegree in a quantitative discipline such as computer science, mathematics, statistics, or engineering\n\nExperience working with entity data (entity resolution / record linkage)\n\nExperience working with data acquisition / data integration\n\nExpertise with Python and the Python data stack (e.g., numpy, pandas)\n\nExperience with streaming platforms (e.g., Kafka)\n\nExperience evaluating data quality and maintaining consistently high data standards across new feature releases (e.g., consistency, accuracy, validity, completeness)\n\nOur Benefits\nStock\n\nCompetitive Salaries\n\nUnlimited paid time off\n\nMedical, dental, & vision insurance\n\nHealth, fitness, and office stipends\n\nThe permanent ability to work wherever and however you want\n\nComp: $180,000-220,000\nPeople 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.\nQualified 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.\nPersonal Privacy Policy for California Residents\nhttps://www.peopledatalabs.com/pdf/privacy-policy-and-notice.pdf","description_format":"text","description_chars":5010,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Vision insurance"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Data Providers & Datasets","B2B Company & Contact Data"],"lifecycle":[{"event":"open","at":"2026-10-27T00:45:37Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring 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