People Data Labs

👥 101-250💰 $45,000,000 Series B about 3 years agoDatabaseArtificial Intelligence (AI)Developer APIsMachine LearningAnalyticsB2BSoftware💼 Private Company
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People Data Labs is a technology company focused on providing data solutions, specializing in people data enrichment and extensive data infrastructure.

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🧭 Full-Time

💸 160000.0 - 180000.0 USD per year

🔍 Data services

  • 5-7+ years of software development experience in platform or cloud infrastructure engineering.
  • 3+ years of experience with Python in a production environment.
  • Strong software development fundamentals and system design experience.
  • Experience with AWS services, including EC2, Lambda, OpenSearch, API Gateway.
  • Familiarity with data stores like Postgres/MySQL, Dynamo, Redis, S3.
  • Experience with Infrastructure-as-code frameworks (e.g., Pulumi, Terraform).
  • Knowledge of network design and Identity and Access Management.
  • Experience with configuration management tools and observability tools such as Datadog.
  • Skilled in CI/CD infrastructure and repo management.
  • Manage and improve AWS and data center infrastructures.
  • Design, implement and maintain a CI/CD pipeline to improve developer workflows.
  • Utilize centralized monitoring and logging for enhanced visibility.
  • Assist development teams in resolving scaling issues and bottlenecks.
  • Manage AWS services, costs, security, and workflows.
  • Collaborate with teammates to develop high-quality software balanced with security and reliability.
Posted 21 days ago
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📍 USA

🧭 Full-Time

💸 175000.0 - 210000.0 USD per year

🔍 Data Solutions

  • 3-5 years of Product Management experience.
  • Prior experience includes iterating on existing programs/processes and scaling the team/organization.
  • Experience working with product, engineering, and other XFN teams to drive end-to-end delivery of projects.
  • Experience leading and guiding leaders in functions who do not report to them to drive execution.
  • Outstanding written and verbal communication/presentation skills through all levels of the organization, technical and non-technical.
  • Ability to understand engineering architecture and facilitate critical decisions with engineering managers and engineers.
  • Experience with project management tools.
  • Works with the leadership team to define the product vision (1-2 years).
  • Analyzes market and competitive data to create products that match or surpass current industry standards.
  • Understands the architecture and technologies used to develop and deliver our products and services.
  • Gathers customer and internal stakeholder feedback to improve the products further.
  • Creates product requirements for the XFN and engineering teams to bring new products to market or enhance existing products and features.
  • Oversees and manages products throughout the product life cycle (concept -> MVP/beta -> GA -> improvements/iterations and deprecations).
  • Owns planning for their strategic area and incorporates feedback from product team members, the engineering team, the XFN team, and customer feedback.
  • Leads trade-off discussions, balancing cost, time, and quality to make informed decisions that align with product goals.

Project ManagementSQLAgileData AnalysisProduct ManagementCross-functional Team LeadershipREST API

Posted 22 days ago
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🔥 Senior Data Engineer
Posted about 2 months ago

📍 USA

🧭 Full-Time

💸 190000.0 - 220000.0 USD per year

🔍 B2B data / Data as a Service (DaaS)

  • 5-7+ years industry experience with strategic technical problem-solving.
  • Strong software development fundamentals.
  • Experience with Python.
  • Expertise in Apache Spark (Java, Scala, or Python-based).
  • Proficiency in SQL.
  • Experience building scalable data processing systems.
  • Familiarity with data pipeline orchestration tools (e.g., Airflow, dbt).
  • Knowledge of modern data design and storage patterns.
  • Experience working in Databricks.
  • Familiarity with cloud computing services (e.g., AWS, GCP, Azure).
  • Experience in data warehousing technologies.
  • Understanding of modern data storage formats and tools.
  • Build infrastructure for ingestion, transformation, and loading of data using Spark, SQL, AWS, and Databricks.
  • Create an entity resolution framework for merging billions of entities into clean datasets.
  • Develop CI/CD pipelines and anomaly detection systems to enhance data quality.
  • Provide solutions to undefined data engineering problems.
  • Assist Engineering and Product teams with data-related technical issues.

AWSPythonSQLKafkaAirflowData engineeringPandasCI/CD

Posted about 2 months ago
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