Data Engineer

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  "last_changed_at": "2026-06-06T07:56:54.952Z",
  "active_status": "deleted"
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{
  "language": "en",
  "location": {
    "raw": "Dallas, TX",
    "city": "Dallas",
    "region": "TX",
    "country": "United States",
    "is_remote": false,
    "confidence": 0.9
  },
  "salary_max": 125000,
  "salary_min": 110000,
  "inferred_at": "2026-06-03T12:27:24.495Z",
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    "language": "en",
    "location": {
      "raw": "Dallas, TX",
      "city": "Dallas",
      "region": "TX",
      "country": "United States",
      "is_remote": false,
      "confidence": 0.9
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    "countries": [
      "United States"
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  "remote_policy": "hybrid",
  "salary_period": "year",
  "workplace_type": "hybrid",
  "salary_currency": "USD"
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{}

{
  "lists": [
    {
      "text": "Information Security Responsibilities",
      "content": "<li>Promote and enforce awareness of key information security practices, including acceptable use of information assets, malware protection, and password security protocols</li><li>Identify, assess, and report security risks, focusing on how these risks impact the confidentiality, integrity, and availability of information assets</li><li>Understand and evaluate how data is stored, processed, or transmitted, ensuring compliance with data privacy and protection standards (GDPR, CCPA, etc.)</li><li>Ensure data protection measures are integrated throughout the information lifecycle to safeguard sensitive information</li>"
    },
    {
      "text": "Responsibilities:",
      "content": "<div>\n<ol type=\"1\" start=\"1\">\n<li><strong>Pipeline Migration</strong></li>\n</ol>\n<ul type=\"disc\">\n<li><strong>Logic &amp; Scheduling:</strong>&nbsp;Refactoring and migrating extraction logic and job scheduling from legacy frameworks&nbsp;to the new Lakehouse environment.</li>\n<li><strong>Data Transfer:</strong>&nbsp;Executing the physical migration of underlying datasets while ensuring data integrity.</li>\n<li><strong>Stakeholder Engagement:</strong> Acting as a technical liaison to internal clients, facilitating \"handoff and&nbsp;sign-off\" conversations with data owners to ensure migrated assets meet business requirements</li>\n\n<ol type=\"1\" start=\"2\">\n<li><strong>Consumption Pattern Migration</strong></li>\n</ol>\n<ul type=\"disc\">\n<li><strong>Code Conversion:</strong>&nbsp;Translating and optimizing legacy SQL and Spark-based consumption patterns (raw and&nbsp;modeled) for compatibility with Snowflake and Iceberg.</li>\n<li><strong>Usage analysis</strong>: Understand usage patterns to deliver the required data products.</li>\n<li><strong>Stakeholder Engagement:</strong>&nbsp;Acting as a technical liaison to internal clients, facilitating \"handoff and&nbsp;sign-off\" conversations with data owners to ensure migrated assets meet business requirements.</li>\n\n<ol type=\"1\" start=\"3\">\n<li><strong>Data Reconciliation &amp; Quality<br><br></strong>A rigorous approach to data validation is required. Candidates must work with reconciliation frameworks to build confidence that migrated data is functionally equivalent to that already used within production flows.</li>\n</ol>\n</ul></ul></div>"
    },
    {
      "text": "Technical Skills:",
      "content": "<div>\n<ol type=\"1\" start=\"1\">\n<li><strong>Basic Qualifications</strong></li>\n</ol>\n<ul type=\"disc\">\n<li><strong>Education:</strong>&nbsp;Bachelor’s or Master’s degree in Computer Science, Applied Mathematics, Engineering, or a&nbsp;related quantitative field.</li>\n<li><strong>Experience:</strong> Minimum of 5 years of professional \"hands-on-keyboard\" coding experience in a collaborative, team-based environment.&nbsp; Ability to trouble shoot&nbsp; (SQL) and basic scripting experience.</li>\n<li><strong>Languages:</strong>&nbsp;Professional proficiency in&nbsp;<strong>Python</strong>&nbsp;or&nbsp;<strong>Java</strong>.</li>\n<li><strong>Methodology:</strong>&nbsp;Deep familiarity with the full Software Development Life Cycle (SDLC) and CI/CD best practices&nbsp;&amp; K8s deployment experience.</li>\n\n<ol type=\"1\" start=\"2\">\n<li><strong>Core Data Engineering Competencies: &nbsp;</strong>Candidates must demonstrate a sophisticated understanding of the&nbsp;following modeling concepts to ensure data correctness during reconciliation:</li>\n</ol>\n<ul type=\"disc\">\n<li><strong>Temporal Data Modeling:</strong>&nbsp;Managing state changes over time (e.g., SCD Type 2).</li>\n<li><strong>Schema Management:</strong>&nbsp;Expertise in&nbsp;Schema Evolution (Ref: Iceberg Apache) and enforcement strategies.</li>\n<li><strong>Performance Optimization:</strong>&nbsp;Advanced knowledge of data partitioning and clustering.</li>\n<li><strong>Architectural Theory:</strong>&nbsp;Balancing Normalization vs. Denormalization and the strategic use of Natural vs.&nbsp;Surrogate Keys.</li>\n\n<ol type=\"1\" start=\"3\">\n<li><strong>Technical Stack Requirements:&nbsp;</strong></li>\n</ol>\n<p style=\"padding-left: 40px;\"><strong>Extraction &amp; Logic: </strong>Kafka, ANSI SQL, FTP, Apache Spark<br><strong>Data Formats:</strong> JSON, Avro, Parquet<br><strong>Platforms:</strong> Hadoop (HDFS/Hive), Snowflake, Apache Iceberg, Sybase IQ</p>\n<p style=\"padding-left: 40px;\">Candidate will also need to work with our internal data management platform, and must have an aptitude for learning new workflows and language constructs is essential.</p>\n</ul></ul></div>"
    }
  ],
  "country": "US",
  "createdAt": 1775658602104,
  "updatedAt": null,
  "categories": {
    "team": "Technology: Data",
    "location": "Dallas, TX",
    "commitment": "Full Time",
    "department": "Data & AI & Cloud",
    "allLocations": [
      "Dallas, TX"
    ]
  },
  "salaryRange": {
    "max": 125000,
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    "currency": "USD",
    "interval": "per-year-salary"
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  "workplaceType": "hybrid"
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