Data Engineering Manager

🕒 June 26

🌵 Arizona, California, +16 more states – Remote

🌵 Arizona – Remote 🏄 California – Remote ⛰️ Colorado – Remote 🐊 Florida – Remote 🐎 Kentucky – Remote 🎰 Nevada – Remote 🏖️ New Jersey – Remote 🌲 North Carolina – Remote 🦀 Maryland – Remote 🚗 Michigan – Remote 🏰 Missouri – Remote 🔔 Pennsylvania – Remote 🌴 South Carolina – Remote 🗿 South Dakota – Remote 🤠 Texas – Remote ⚔️ Virginia – Remote ☕ Washington – Remote 🦬 Wyoming – Remote

💵 $172.8k - $206.1k / year

⏰ Full Time

🟠 Senior

🔴 Lead

👮‍♀️ Software Engineering Manager

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Spokeo

WebsiteLinkedInAll Job Openings

51 - 200 employees

👥 B2C

☁️ SaaS

🔌 API

B2C • SaaS • API

<Spokeo> is a people-search and data aggregation service that lets users search by name, phone, email, or address to find contact information, location history, social profiles, property records, court records, and other public records. It combines billions of records from consumer and industry sources into concise, easy-to-read reports, offers account-based report updates, enterprise search capabilities, and an API for integration. Spokeo is positioned for individual consumers seeking to reconnect, identify callers, or verify sellers, while also offering paid services and tools for businesses; it states it is not an FCRA consumer reporting agency.

📋 Description

• Lead and manage data engineers to build data solutions for our business intelligence needs • Lead a cross-functional team in building a state-of-the-art data analytics platform • Collaborate with data scientists, analysts, product managers, and executives to understand and fulfill our data needs • Lead database development, data pipeline, integration, ETL, modeling, and data architecture using AWS technologies • Define and manage SLA’s for all data sets and reporting processes • Develop software engineering best practices, guidelines, procedures, and repeatable and scalable frameworks • Document, automate, and enforce data quality, data integrity, and QA best practices

🎯 Requirements

• 7+ years of experience in Business Intelligence and Data Warehousing • 5+ years of experience with cloud solutions (AWS, Azure) • 5+ years of experience with big data technologies (Spark, Hadoop, MapReduce, Hive, Kafka) • 5+ years of experience with data pipelines orchestration tools like Airflow. • 2+ years of experience managing data engineering teams, providing technical guidance, and mentoring data engineers. • Expertise in data lakes, warehouses, modeling, ETL, and big data platforms. • Familiarity with MLOps to help design, automate, and streamline the entire lifecycle of ML models. • Expertise in RDBMS, SQL, query optimization, and security • A Bachelor’s degree in Computer Science, Information Management, or a related field • Attention to detail, excellent problem-solving ability, and strong communication skills.

🏖️ Benefits

• annual bonus program • stock options • 401K matching • 100% medical/dental/vision coverage • unlimited PTO • mental health resources • paid home office equipment • fitness reimbursements • support paying for courses and more