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Remote Data Conversion Developer Jobs in Garden Grove, CA

Hyundai Capital

Software Developer (Salesforce)

Irvine, CA · On-site +1

$59.50 - $79/hr

Support data migration, conversion, and bulk processing activities. * Resolve data-related issues ... Hybrid flexibility - 4 days in office, 1 day remote * Vehicle perks - monthly vehicle allowance ...

NextDeavor Inc.

Principal Data Architect

Irvine, CA · Remote

$126K - $214K/yr

You will partner with product, engineering, analytics, ML, finance, risk, and customer-facing teams to translate needs into durable data designs. This is a hands-on, remote role where you will both ...

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All JobsData Conversion Developer JobsRemote Data Conversion Developer JobsRemote Data Conversion Developer Jobs in Garden Grove, CA

Remote Data Conversion Developer information

See Garden Grove, CA salary details

$11.1K

$111.4K

$141.3K

How much do remote data conversion developer jobs pay per year?

As of Aug 8, 2026, the average yearly pay for remote data conversion developer in Garden Grove, CA is $111,393.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,100.00 and $136,700.00 per year, depending on experience, location, and employer.

What is the difference between Remote Data Conversion Developer vs Data Analyst?

AspectRemote Data Conversion DeveloperData Analyst
Required CredentialsTypically requires programming skills, data conversion tools, and sometimes certifications in data managementRequires analytical skills, proficiency in data visualization, and often a degree in statistics or related fields
Work EnvironmentPrimarily technical, focused on data transformation, ETL processes, and scriptingAnalytical, focused on interpreting data, creating reports, and providing insights
Employer & Industry UsageUsed in IT, data management, and software development sectorsCommon in finance, marketing, healthcare, and business intelligence sectors

The main difference is that Remote Data Conversion Developers focus on transforming and converting data using technical skills, while Data Analysts interpret and analyze data to support decision-making. Both roles may work remotely and require familiarity with data tools, but their core responsibilities differ significantly.

What are the key skills and qualifications needed to thrive as a remote data conversion developer?

To thrive as a Remote Data Conversion Developer, you need strong programming skills (often in SQL, Python, or ETL tools), data mapping expertise, and an understanding of database structures, typically backed by a degree in computer science or related experience. Familiarity with data conversion platforms such as Informatica, Talend, or SSIS, and certifications in relevant tools or cloud services, are commonly required. Excellent problem-solving, attention to detail, and effective communication are crucial soft skills for collaborating remotely and managing complex data processes. These skills ensure accurate, efficient data transformations and seamless integration across diverse systems in a distributed work environment.

What is a remote data conversion developer?

A Remote Data Conversion Developer is a professional who specializes in transforming data from one format or system to another, often working from a remote location. Their main responsibilities include analyzing existing data structures, designing conversion processes, writing scripts or software to automate data migration, and ensuring data integrity during the conversion. They typically work with databases, data warehouses, or legacy systems to facilitate seamless data transitions during system upgrades or platform changes. Strong skills in programming, data analysis, and problem-solving are essential for this role.

What are some common challenges faced by remote data conversion developers when working with legacy data systems?

Remote Data Conversion Developers often encounter challenges such as inconsistent data formats, incomplete or corrupted datasets, and undocumented legacy systems. Successfully converting and migrating data requires problem-solving skills to map and validate data accurately, as well as strong communication with business analysts and system owners to clarify requirements and resolve ambiguities. Additionally, thorough testing and quality assurance are essential to ensure data integrity throughout the conversion process.
What cities near Garden Grove, CA are hiring for Remote Data Conversion Developer jobs? Cities near Garden Grove, CA with the most Remote Data Conversion Developer job openings:
Remote Data Conversion Developer jobs near you

Data Scientist, AI Data Foundations

NextDeavor Inc.

Irvine, CA • Remote

$114K - $175K/yr

Contractor

Re-posted 6 days ago

Job description

Data Scientist, AI Data Foundations
Full-time
Remote
Exclusive confidential search — details shared with qualified applicants.
 
Become a Key Player as a Data Scientist, AI Data Foundations

You will design and build the curated data structures that AI and ML applications consume, enabling higher-quality model training and inference. You will partner with model builders, product, risk, and growth stakeholders to surface actionable insights and ship production-ready vector, feature, and graph data assets. This is a Remote role.

Here's How You'll Make an Impact on the Team
  • Build and maintain vector stores for RAG, including embedding pipelines, chunking strategies, indexing, and refresh patterns.
  • Own the feature store: design, build, and operate feature definitions, freshness SLAs, lineage, and point-in-time correctness for offline/online use.
  • Design and implement graph data structures to model relationships across applicants, applications, products, lenders, decisions, and outcomes.
  • Lead data discovery: profile lending, deposit, and behavioral datasets to identify trends, segments, anomalies, and model drivers; produce actionable hypotheses for stakeholders.
  • Engineer curated, AI-ready datasets with appropriate quality checks, documentation, and governance for downstream model builders and analysts.
  • Define and run evaluation frameworks for RAG retrieval quality, feature drift, embedding quality, and graph completeness; iterate on metrics.
  • Partner closely with ML engineers and applied scientists to ensure data assets accelerate model development and serving workflows.
  • Champion responsible data use by collaborating with governance, security, and compliance teams to ensure data classification, consent, and regulatory boundaries are respected.
  • Communicate findings via write-ups, notebooks, dashboards, and short presentations for technical and non-technical audiences.
Here's What You'll Need to Be Successful in This Role
  • 4–7 years of experience in data science, ML engineering, or applied data roles, with significant time building data assets consumed by models or applications.
  • Hands-on experience designing and operating vector stores for RAG or semantic search (embedding generation, chunking, indexing, retrieval evaluation).
  • Experience building or operating a feature store (e.g., Databricks Feature Store, Feast, or custom), including offline training and online serving patterns and point-in-time correctness.
  • Experience modeling and building graph data structures and writing graph queries (Neo4j, TigerGraph, Cosmos DB Gremlin, or similar).
  • Strong proficiency in Python (pandas, NumPy, scikit-learn, PySpark) and SQL; comfortable using Databricks notebooks and jobs.
  • Practical experience with embedding models and LLM tooling (Hugging Face, OpenAI/Azure OpenAI APIs, LangChain or similar) in production or near-production contexts.
  • Demonstrated data discovery skills: profiling messy datasets, surfacing patterns, validating findings statistically, and explaining results clearly.
  • Solid grounding in classical ML concepts (supervised vs. unsupervised learning, train/test discipline, leakage, evaluation metrics).
  • Strong written and verbal communication skills for technical and business audiences.
Here's What Else Might Help You Out
  • Experience in SaaS or FinTech, especially with lending, deposit, credit, fraud, or KYC/AML data.
  • Familiarity with Databricks-native AI/ML tooling: Databricks Vector Search, Databricks Feature Store, MLflow, Unity Catalog.
  • Experience with open-source vector DBs (pgvector, Pinecone, Weaviate, Chroma, FAISS) and strong opinions on trade-offs.
  • Experience with Microsoft Azure data and AI services (Azure OpenAI, Azure AI Search, ADLS Gen2).
  • Experience evaluating RAG systems end-to-end (recall@k, faithfulness, answer quality, hallucination measurement).
  • Exposure to graph algorithms (community detection, link prediction, centrality) applied to business problems.
  • Bachelor's or Master's in CS, Statistics, Mathematics, Engineering, or related quantitative field, or equivalent experience.
Pay Range

$114,000 - $175,000/year

Ready to Make Your Mark?

This role may fill quickly. Submit your resume to be considered.

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