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Independent Contractor Databricks Jobs (NOW HIRING)

... Databricks). * Vector Expertise: Hands-on experience with at least one major Vector Database and ... This position is not available for independent contractors No applications will be considered if ...

Data Modeler

Harrisburg, PA · On-site

$54 - $70/hr

The contractor must demonstrate experience in: * Development, validation, publication, and ... Working knowledge of Azure Databricks, Delta Lake, Synapse, and Python. * Experience evaluating ...

Posted today

Data Modeler

Harrisburg, PA · On-site

$54 - $70/hr

The contractor must demonstrate experience in: * Development, validation, publication, and ... Working knowledge of Azure Databricks, Delta Lake, Synapse, and Python. * Experience evaluating ...

Posted today

Associate Director, AI/ML Engineering

Cambridge, MA · On-site

$64K - $65K/yr

Experience with Claude Code, Databricks, and GCP is nice to have #EligibleforERP Required Skills ... As a federal contractor, we comply with all affirmative action requirements for protected veterans ...

Sr Lead Software Engineer

Columbus, OH · On-site

$120 - $180/hr

... contractors, and vendors * Develops secure and high-quality production code, and reviews and debugs ... Ability to tackle design and functionality problems independently with little to no oversight

Showing results 41-60

Independent Contractor Databricks information

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$394

$1.1K

$2.1K

How much do independent contractor databricks jobs pay per week?

As of Aug 12, 2026, the average weekly pay for independent contractor databricks in the United States is $1,089.33, according to ZipRecruiter salary data. Most workers in this role earn between $721.15 and $1,211.54 per week, depending on experience, location, and employer.

What skills and qualifications are needed to thrive as an independent contractor Databricks?

To thrive as an Independent Contractor Databricks, you need a solid background in data engineering, big data analytics, and proficiency with Apache Spark, typically supported by a degree in computer science or a related field. Familiarity with Databricks platform, cloud services (such as AWS or Azure), and relevant certifications like Databricks Certified Data Engineer are highly beneficial. Strong problem-solving, communication, and self-management skills help you deliver solutions independently and collaborate effectively with clients. These skills are essential for delivering robust data solutions, meeting client expectations, and staying competitive in a rapidly evolving data landscape.

What is the difference between Independent Contractor Databricks vs Data Engineer?

AspectIndependent Contractor DatabricksData Engineer
CredentialsOften requires Databricks certifications, SQL, Python, cloud platform knowledgeRequires similar certifications, SQL, Python, cloud skills, sometimes specific to cloud providers
Work EnvironmentFreelance, project-based, remote or on-siteFull-time, corporate or tech company, hybrid or on-site
Employer & IndustryClients across industries, consulting firms, startupsTech companies, finance, healthcare, large enterprises

While both roles require data processing skills and cloud platform knowledge, Independent Contractor Databricks typically involves project-based freelance work with a focus on Databricks platform expertise. Data Engineers often work full-time within organizations, handling broader data pipeline responsibilities. The key difference lies in employment status and work setup.

What is an independent contractor Databricks?

Independent Contractor Databricks are professionals who work on a contract basis, rather than as full-time employees, to provide expertise using Databricks' unified analytics platform. They are typically hired by organizations to help with data engineering, machine learning, and big data analytics projects, leveraging Databricks' capabilities on Apache Spark. These contractors often bring specialized knowledge in cloud platforms, data pipelines, and advanced analytics, working independently or as part of project teams. Their flexible engagement allows companies to scale their data initiatives without committing to permanent hires.

What are common challenges faced by independent contractor Databricks professionals when onboarding with new clients?

Independent Contractor Databricks professionals often encounter challenges such as adapting to diverse data environments and integrating Databricks with existing infrastructure. Each client may have unique data governance policies, security requirements, and legacy systems, requiring contractors to quickly learn and align with these standards. Additionally, contractors must efficiently communicate with both technical and non-technical stakeholders to understand project goals and deliver value within tight timelines. Building rapport with in-house teams and demonstrating expertise early on can help overcome these onboarding hurdles.
More about Independent Contractor Databricks jobs
What cities are hiring for Independent Contractor Databricks jobs? Cities with the most Independent Contractor Databricks job openings:
What are the most commonly searched types of Databricks jobs? The most popular types of Databricks jobs are:
What states have the most Independent Contractor Databricks jobs? States with the most job openings for Independent Contractor Databricks jobs include:
Infographic showing various Independent Contractor Databricks job openings in the United States as of August 2026, with employment types broken down into 100% Contract. Highlights an 100% In-person job distribution, with an average salary of $56,645 per year, or $27.2 per hour.

Data Lead- Dallas, TX

Photon

Dallas, TX • On-site

Full-time, Contractor

Medical, Dental, Vision, Retirement, PTO

Re-posted 29 days ago


Job description


We are seeking a Lead Data Engineer to build and scale the data infrastructure powering our Agentic AI products. You will be responsible for the "Ingestion-to-Insight" pipeline that allows autonomous agents to access, search, and reason over vast amounts of proprietary and public data.
Your role is critical: you will design the RAG (Retrieval-Augmented Generation) architectures and data pipelines that ensure our agents have the right context at the right time to make accurate decisions.
Key Responsibilities
  • AI-Ready Data Pipelines: Design and implement scalable ETL/ELT pipelines that process both structured (SQL, logs) and unstructured (PDFs, emails, docs) data specifically for LLM consumption.
  • Vector Database Management: Architect and optimize Vector Databases (e.g., Pinecone, Weaviate, Milvus, or Qdrant) to ensure high-speed, relevant similarity searches for agentic retrieval.
  • Chunking & Embedding Strategies: Collaborate with AI Engineers to optimize data chunking strategies and embedding models to improve the "recall" and "precision" of the agent's knowledge retrieval.
  • Data Quality for AI: Develop automated "Data Cleaning" workflows to remove noise, PII (Personally Identifiable Information), and toxicity from training/context datasets.
  • Metadata Engineering: Enrich raw data with advanced metadata tagging to help agents filter and prioritize information during multi-step reasoning tasks.
  • Real-time Data Streaming: Build low-latency data streams (using Kafka or Flink) to provide agents with "fresh" data, enabling them to act on real-time market or operational changes.
  • Evaluation Frameworks: Construct "Gold Datasets" and versioned data snapshots to help the team benchmark agent performance over time.

Required Skills & Qualifications
  • Experience: 10+ years in Data Engineering, with at least 2 years focusing on data for LLMs or AI/ML applications.
  • Python Mastery: Deep expertise in Python (Pandas, Pydantic, FastAPI) for data manipulation and API integration.
  • Data Tooling: Strong experience with modern data stack tools (e.g., dbt, Airflow, Dagster, Snowflake, or Databricks).
  • Vector Expertise: Hands-on experience with at least one major Vector Database and knowledge of similarity search algorithms (HNSW, Cosine Similarity).
  • Search Knowledge: Familiarity with hybrid search techniques (combining semantic search with traditional keyword search like Elasticsearch/BM25).
  • Cloud Infrastructure: Proficiency in managing data workloads on AWS, Azure, or GCP.

Preferred Qualifications
  • Experience with LlamaIndex or LangChain for data ingestion.
  • Knowledge of Graph Databases (e.g., Neo4j) to help agents understand complex relationships between data points.
  • Familiarity with "Data-Centric AI" principles-prioritizing data quality over model size.

Compensation, Benefits and Duration
Minimum Compensation: USD 46,000
Maximum Compensation: USD 162,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees.
This position is not available for independent contractors
No applications will be considered if received more than 120 days after the date of this post