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Time Series Jobs (NOW HIRING)

Artius Solutions

Senior Data Engineer

New York, NY · On-site

$120K - $121K/mo

The ideal candidate will have deep expertise in time series data platforms and strong proficiency in integrating data pipelines with machine learning workflows. This role involves collaboration with ...

Inherent Technologies

Data Scientist

Chandler, AZ · Remote

Strong Time Series forecasting, ML, deep learning and standard statistical methods to evaluate models. Experience working on supply chain projects. We are seeking a highly skilled Data Scientist to ...

Staffingine LLC

Azure OT Architect with LoRaWAN

Houston, TX · On-site

$60.75 - $79/hr

Define data models and ingestion pipelines for time series data from diverse sensor ecosystems * Collaborate with cross functional teams to ensure seamless integration between OT systems and ...

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How much do time series jobs pay per year?

As of Jul 8, 2026, the average yearly pay for time series in the United States is $74,448.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,000.00 and $88,000.00 per year, depending on experience, location, and employer.
What cities are hiring for Time Series jobs? Cities with the most Time Series job openings:
What states have the most Time Series jobs? States with the most job openings for Time Series jobs include:
Infographic showing various Time Series job openings in the United States as of July 2026, with employment types broken down into 87% Full Time, 11% Part Time, 1% Temporary, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $74,448 per year, or $35.8 per hour.

Graph and Time Series Database Specialist

Futran Tech Solutions Pvt. Ltd.

Plano, TX • On-site

Full-time

Re-posted 21 days ago

Job description

Title: Graph and Time Series Database Specialist
Location: Plano, Texas (Onsite Role)
Need Local Candidates Only
Position Overview:
We are seeking a highly skilled and motivated Graph and Time Series Database Specialist to join our dynamic team. As a specialist in graph and time series databases, you will play a critical role in designing, implementing, optimizing, and maintaining our data storage solutions. Your expertise will help drive innovation, enhance data performance, and support our organization's data-driven decision-making processes.
Key Responsibilities:
1. Database Design and Implementation:
• Collaborate with cross-functional teams to understand data requirements and design appropriate graph and time series database schemas.
• Implement and configure graph and time series databases to meet specific application needs.
• Ensure data integrity, consistency, and security across databases.
2. Query Optimization and Performance Tuning:
• Analyze and optimize query performance for graph traversal and time series data retrieval.
• Identify and resolve bottlenecks to improve overall database performance.
• Monitor and fine-tune database parameters to enhance system efficiency.
3. Data Modeling:
• Develop and maintain data models for graph and time series data structures.
• Map complex relationships and hierarchies for efficient graph traversals.
• Define retention policies and storage strategies for time series data.
4. Data Integration:
• Integrate graph and time series databases with existing systems and applications.
• Implement data pipelines for seamless data ingestion and synchronization.
• Work with ETL processes to ensure timely and accurate data updates.
5. Security and Compliance:
• Implement security measures to protect sensitive data stored in the graph and time series databases.
• Ensure compliance with relevant data protection regulations and industry standards.
Troubleshooting and Maintenance:
• Monitor database health and diagnose and resolve issues as they arise.
Required Qualifications:
• Bachelor's degree in computer science, Information Technology, or a related field.
• Proven development experience with in Graph database technologies (e.g., Neo4j, Amazon Neptune), Time Series databases (e.g., InfluxDB, TimescaleDB, AWS Timestream), NOSQL (eg., AWS DynamoDB, MongoDB) and In-memory(eg., AWS MemoryDB for Redis)
• Graph Query Languages like openCypher, Gremlim or SPARQL.
• Proficiency in Python programming.
• Solid knowledge of graph database concepts, including graph data modeling, traversal algorithms, etc.
• Exeprience in GraphDB tuning techniques, eg: partitioning and sharding, create and use indexes, Query profiling, Configure the page cache, Configuration parameters and memory tuning, garbage collection, etc.
• Implement data ingestion pipelines to efficiently capture and store real-time and historical time series data from various sources.
• Design and develop time series database architectures that efficiently manage high-frequency, chronological data.
• Proficiency in database design, query optimization, and performance tuning.
• Strong understanding of data modeling principles for graph structures and time-based data.
• Familiarity with real-time data processing frameworks (e.g., Kafka, Apache Flink) is a plus.
• Excellent problem-solving and troubleshooting skills.
• Strong communication and collaboration abilities.
• Ability to work independently and manage multiple tasks simultaneously.
• Preferred certifications: Neo4j Certified Professional, InfluxData Certified Professional, etc.

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