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Data Reconciliation Jobs (NOW HIRING)

Hudson Data LLC

Data Quality Analyst

Trenton, NJ · On-site

This role requires a balance of building automated checks and performing hands-on manual data reconciliation to quickly isolate anomalies. * Build and maintain scalable test automation frameworks ...

ScrumLink, Inc.

Data Architect

Manhattan, NY · On-site

$70.25 - $90.50/hr

Key Skills: AWS (Glue, DMS, S3, DynamoDB, Lake Formation) Apache Kafka/MSK & Kafka Connect/Debezium PySpark, Flink & Streaming ETL CDC, Data Reconciliation & Iceberg Event-Driven Architecture ...

Encoded Therapeutics

Clinical Data Manager

$110K - $135K/yr

Reconcile complex datasets from multiple external vendors with the EDC and internal systems; meticulously track, document, and resolve discrepancies to ensure an easy-to-audit framework.

Lorven Technologies

Data Analyst

Dallas, TX · On-site

SQL knowledge which includes having very good knowledge of Data reconciliation, proficiency in SQL queries - writing complex queries in Postgres and Snowflake.

New

Photon

Java/API Lead - Jersey City

Jersey City, NJ · On-site

Java Data Reconciliation Engineer Summary: We're seeking a skilled Java Data Reconciliation Engineer to join our team and drive the development of robust data reconciliation solutions within our ...

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How much do data reconciliation jobs pay per hour?

As of Jul 22, 2026, the average hourly pay for data reconciliation in the United States is $21.84, according to ZipRecruiter salary data. Most workers in this role earn between $18.99 and $24.62 per hour, depending on experience, location, and employer.

What is the highest paying job in data analytics?

In data analytics, senior roles such as Data Science Manager, Director of Data Analytics, or Chief Data Officer typically have the highest salaries, often exceeding six figures annually. These positions require advanced skills in statistical analysis, machine learning, and leadership, along with extensive experience and certifications.

What is a data reconciliation?

Data reconciliation is the process used by data reconciliation specialists to compare and adjust data from different sources to ensure accuracy and consistency. It often involves using tools like spreadsheets or specialized software to identify discrepancies and correct errors, supporting data integrity in financial, operational, or reporting environments.

Is reconciliation a good career?

Data reconciliation is a valuable career in finance, accounting, and data management, involving comparing and matching data sets to ensure accuracy. It requires attention to detail, analytical skills, and proficiency with tools like Excel or reconciliation software. The role often offers stable employment and opportunities for advancement in various industries.

What are typical daily responsibilities of a Data Reconciliation professional?

A Data Reconciliation professional is responsible for comparing and verifying data across different systems or sources to identify and resolve discrepancies. Day-to-day tasks may include reviewing transaction records, preparing reconciliation reports, following up on unmatched items, and collaborating with internal departments such as accounting, operations, or IT for resolution. They also document reconciliation processes and may recommend improvements to increase accuracy and efficiency. This role often requires managing tight deadlines and maintaining high standards of data quality, making strong organizational skills essential.

What are the key skills and qualifications needed to thrive in the Data Reconciliation position, and why are they important?

To thrive in a Data Reconciliation role, you need strong analytical abilities, attention to detail, and a solid understanding of data management principles, often supported by a degree in finance, accounting, or a related field. Experience with reconciliation software, ERP systems, advanced Excel functions, and sometimes certifications in accounting or data analysis are highly valued. Excellent problem-solving skills, effective communication, and a collaborative attitude set top performers apart. These competencies ensure accurate data matching, quick resolution of discrepancies, and the integrity of financial or operational records.

What skills do you need to be a reconciliation specialist?

A reconciliation specialist needs strong attention to detail, analytical skills, and proficiency with accounting software and spreadsheets. Good communication skills and the ability to work under tight deadlines are also important for accurately matching and verifying financial data.

What is a Data Reconciliation job?

A Data Reconciliation job involves comparing and verifying data from different sources to ensure accuracy and consistency. Professionals in this role identify discrepancies, correct errors, and ensure that records align across databases, financial reports, or operational systems. This process is crucial in industries like finance, healthcare, and logistics to maintain data integrity and compliance with regulations. Strong analytical skills, attention to detail, and proficiency in data management tools are essential for success in this role.

More about Data Reconciliation jobs
What cities are hiring for Data Reconciliation jobs? Cities with the most Data Reconciliation job openings:
What are the most commonly searched types of Data Reconciliation jobs? The most popular types of Data Reconciliation jobs are:
What states have the most Data Reconciliation jobs? States with the most job openings for Data Reconciliation jobs include:
What job categories do people searching Data Reconciliation jobs look for? The top searched job categories for Data Reconciliation jobs are:
Data Reconciliation jobs near you
Infographic showing various Data Reconciliation job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $45,429 per year, or $21.8 per hour.
SPARK Data Reconciliation Engineer- NJ

SPARK Data Reconciliation Engineer- NJ

Photon

Addison, TX • On-site

Full-time

Re-posted 18 days ago

Job description


Job Title: PySpark Data Reconciliation Engineer
Summary:
We're seeking a skilled PySpark Data Reconciliation Engineer to join our team and drive the development of robust data reconciliation solutions within our financial systems. You will be responsible for designing, implementing, and maintaining PySpark-based applications to perform complex data reconciliations, identify and resolve discrepancies, and automate data matching processes. The ideal candidate possesses strong PySpark development skills, experience with data reconciliation techniques, and the ability to integrate with diverse data sources and rules engines.
Key Responsibilities:
Data Reconciliation Development:
  • Design, develop, and test PySpark-based applications to automate data reconciliation processes across various financial data sources, including relational databases, NoSQL databases, batch files, and real-time data streams.
  • Implement efficient data transformation, matching algorithms (deterministic and heuristic) using PySpark and relevant big data frameworks.
  • Develop robust error handling and exception management mechanisms to ensure data integrity and system resilience within Spark jobs.

Data Analysis and Matching:
  • Collaborate with business analysts and data architects to understand data requirements and matching criteria.
  • Analyze and interpret data structures, formats, and relationships to implement effective data matching algorithms using PySpark.
  • Work with distributed datasets in Spark, ensuring optimal performance for large-scale data reconciliation.

Rules Engine Integration:
  • Integrate PySpark applications with rules engines (e.g., Drools) or equivalent to implement and execute complex data matching rules.
  • Develop PySpark code to interact with the rules engine, manage rule execution, and handle rule-based decision-making.

Problem Solving and Gap Analysis:
  • Collaborate with cross-functional teams to identify and analyze data gaps and inconsistencies between systems.
  • Design and develop PySpark-based solutions to address data integration challenges and ensure data quality.
  • Contribute to the development of data governance and quality frameworks within the organization.

Qualifications and Skills:
  • Bachelor's degree in Computer Science or a related field.
  • 5+ years of hands-on experience in big data development, preferably with exposure to data-intensive applications.
  • Strong understanding of data reconciliation principles, techniques, and best practices.
  • Proficiency in PySpark, Apache Spark, and related big data technologies for data processing and integration.
  • Experience with rules engine integration and development
  • Strong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.
  • Excellent communication and collaboration skills to work effectively with business analysts, data architects, and other team members.
  • Familiarity with data streaming platforms (e.g., Kafka, Kinesis) and big data technologies (e.g., Hadoop, Hive, HBase) is a plus.

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