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Data Processing Manager Jobs in Maynard, MA (NOW HIRING)

Novartis

Scientific Data Engineer

Cambridge, MA · Hybrid

$103K - $192K/yr

... management, including documentation, versioning, and traceable update processes * Assess dataset ... Experience with data wrangling, data quality control, and reproducible analysis workflows

Verisk

Data Architect

Boston, MA · On-site

$160K - $175K/yr

Lead the architecture, design, and implementation of cloud-native data platforms - including ingestion, storage, processing, metadata management, governance, and analytics enablement. * Define and ...

Verisk Analytics

Data Architect (Boston)

Boston, MA · On-site

$69.25 - $89/hr

Lead the architecture, design, and implementation of cloud‑native data platforms -- including ingestion, storage, processing, metadata management, governance, and analytics enablement. * Define and ...

Pwc

Data Validation Risk - Manager

Boston, MA

$99K - $232K/yr

As a Manager, you will lead teams and manage client accounts, focusing on strategic planning and ... Accounting, Engineering, Data Processing/Analytics/Science, Computer and Information Science ...

Pwc

Data Engineer - Senior Manager

Boston, MA

$124K - $280K/yr

In data engineering at PwC, you will focus on designing and building data infrastructure and ... As a Senior Manager you lead large projects, innovate processes, and maintain operational ...

Pwc

Data Engineer - Senior Associate

Boston, MA

$77K - $202K/yr

... processing and workflow management - Building and managing data lakes and warehouses to support large-scale data storage and retrieval - Confirming data quality and validation through rigorous ...

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Data Processing Manager information

See Maynard, MA salary details

$36.5K

$55.5K

$72.4K

How much do data processing manager jobs pay per year?

As of Jul 12, 2026, the average yearly pay for data processing manager in Maynard, MA is $55,500.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,900.00 and $66,100.00 per year, depending on experience, location, and employer.

What are the typical challenges faced by a Data Processing Manager when overseeing large-scale data projects?

Data Processing Managers often encounter challenges such as ensuring data quality and consistency across multiple sources, managing tight project deadlines, and coordinating with cross-functional teams like IT, analytics, and compliance. They must stay updated on evolving data processing technologies while maintaining security and privacy standards. Effective communication and adaptability are essential, as priorities may shift quickly based on organizational needs or data integrity issues.

What are the key skills and qualifications needed to thrive as a Data Processing Manager, and why are they important?

To thrive as a Data Processing Manager, you need expertise in data management, analysis, and process optimization, typically supported by a degree in computer science, information systems, or a related field. Familiarity with database management systems (DBMS), ETL tools, and data governance frameworks, along with certifications like Certified Data Management Professional (CDMP), is often required. Strong leadership, problem-solving, and communication skills help you effectively lead teams and collaborate across departments. These skills are crucial for ensuring data integrity, efficient workflows, and informed decision-making within an organization.

Are data managers in demand?

Data processing managers are in high demand due to the increasing reliance on data-driven decision making across industries. They typically require strong analytical skills, knowledge of data management tools, and experience with data governance, making their roles essential in organizations seeking to optimize data workflows.

What is the highest paying job in data?

In data-related fields, executive roles such as Chief Data Officer (CDO) or Chief Data Scientist tend to be the highest paying, often earning six-figure salaries or more. These positions require extensive experience, leadership skills, and expertise in data strategy, analytics, and governance.

Is a data processor a stressful job?

A data processing manager role can be stressful due to tight deadlines, high accuracy requirements, and managing large volumes of data. The job often involves attention to detail, problem-solving skills, and working with data management tools, which can contribute to workload pressure.

What does a Data Processing Manager do?

A Data Processing Manager oversees the collection, organization, and analysis of data within an organization. They coordinate data workflows, ensure data quality, and implement processing systems using tools like SQL, Python, or data management software. The role often requires strong leadership, problem-solving skills, and knowledge of data security and compliance standards.
What job categories do people searching Data Processing Manager jobs in Maynard, MA look for? The top searched job categories for Data Processing Manager jobs in Maynard, MA are:
What cities near Maynard, MA are hiring for Data Processing Manager jobs? Cities near Maynard, MA with the most Data Processing Manager job openings:
Data Processing Manager jobs near you
Sr Data Engineer- Data Platform & AI Enablement

Sr Data Engineer- Data Platform & AI Enablement

Citizens

Boston, MA

$124K - $149K/yr

Full-time

Posted 6 days ago

Job description

Senior Data Engineer - Enterprise Data Enablement

The Enterprise Data Enablement team is seeking a Senior Data Engineer who can design, develop, and maintain secure, scalable, and efficient data pipelines and platforms. This role will focus on building and deploying data solutions across financial consumer business domains by leveraging existing and new data framework capabilities to acquire, transform, stream, and integrate data. The candidate will also contribute to innovative data engineering solutions, including AI/GenAI/Agentic AI-ready data capabilities, while collaborating with and supporting a team of data engineers in building scalable, secure, and intelligent data platforms.

Primary Responsibilities
  • Design, build, and maintain reliable, efficient, and scalable data pipelines to acquire, transform, and store large datasets.
  • Develop robust data pipelines to collect, process, and compute metrics from various financial data sources while adhering to quality and development standards.
  • Contribute to application architecture and technical solutions, and help implement data framework patterns alongside senior engineers and architects.
  • Collaborate with cross-functional teams to deliver optimal data solutions that meet business and platform needs.
  • Develop and deploy high-quality, production-ready code.
  • Apply strong database design principles and data modeling techniques to translate business requirements into scalable data solutions.
  • Develop and optimize data models to support analytics, reporting, machine learning, and AI-driven use cases.
  • Support the implementation and enhancement of enterprise data frameworks and contribute to scalable solutions.
  • Identify opportunities to improve existing frameworks and help build reusable capabilities across the organization.
  • Troubleshoot and resolve data-related issues in a timely manner.
  • Execute unit testing for data pipelines, validate results, and ensure data quality and accuracy; partner with business users for User Acceptance Testing and support deployment activities.
  • Follow change management practices and ensure adherence to compliance and regulatory standards.
  • Design and build data pipelines and platform capabilities that support AI, Generative AI, and Agentic AI use cases, including model training, inference, retrieval, and orchestration workflows.
  • Enable AI-ready data foundations by developing high-quality, governed, and reusable datasets for machine learning, large language model (LLM), and intelligent automation solutions.
  • Develop and optimize pipelines for structured, semi-structured, and unstructured data to support GenAI use cases such as semantic search, document intelligence, and retrieval-augmented generation (RAG).
  • Partner with data scientists, ML engineers, architects, and product teams to integrate AI/GenAI capabilities into enterprise data platforms and workflows.
  • Implement metadata, lineage, governance, security, and access controls required for responsible AI and enterprise-scale GenAI adoption.
  • Ensure observability, reliability, performance, and data quality for data pipelines, including those supporting AI-enabled workflows.
Required Skills / Experience
  • 6-8+ years of experience in data engineering and distributed data processing technologies.
  • Hands-on experience with streaming technologies such as Apache Spark, Beam, or Flink.
  • Experience with message brokers such as Apache Kafka.
  • Experience working with microservices and batch processing systems.
  • Strong programming skills in Java and/or Scala; Python experience preferred.
  • Strong SQL development and performance optimization skills.
  • Solid knowledge of relational databases (Redshift, PostgreSQL, Snowflake) and NoSQL databases (MongoDB or similar).
  • Experience with CI/CD pipelines and version control systems such as Bitbucket and Git.
  • Experience with ETL development tools such as Talend or DataStage is a plus.
  • Experience with Java Spring Boot; familiarity with React, TypeScript, or Angular is a plus.
  • Understanding of cloud-based data processing, with AWS and/or Azure experience preferred.
  • Experience building data pipelines that support analytics, machine learning, and AI workloads.
  • Working knowledge of data engineering concepts supporting LLM-based applications, including retrieval pipelines, embeddings workflows, and unstructured data processing.
  • Familiarity with AI/GenAI concepts such as RAG, semantic search, document processing, and model inference workflows.
  • Understanding of data governance, security, lineage, and compliance requirements, particularly in regulated environments.
  • Exposure to workflow orchestration frameworks and automation patterns is a plus.
  • Exposure to vector databases, semantic models, or MLOps/LLMOps concepts is a plus.
  • Strong analytical and problem-solving skills, with the ability to collaborate effectively within technical teams.
Education, Certifications, and/or Other Professional Credentials
  • Bachelor's degree in Computer Science, Engineering, or a related technology field
Hours and Work Schedule
  • Hours per Week: 40
  • Work Schedule: Monday through Friday

Equal Employment Opportunity

Citizens, its parent, subsidiaries, and related companies (Citizens) provide equal employment and advancement opportunities to all colleagues and applicants for employment without regard to age, ancestry, color, citizenship, physical or mental disability, perceived disability or history or record of a disability, ethnicity, gender, gender identity or expression, genetic information, genetic characteristic, marital or domestic partner status, victim of domestic violence, family status/parenthood, medical condition, military or veteran status, national origin, pregnancy/childbirth/lactation, colleague's or a dependent's reproductive health decision making, race, religion, sex, sexual orientation, or any other category protected by federal, state and/or local laws. At Citizens, we are committed to fostering an inclusive culture that enables all colleagues to bring their best selves to work every day and everyone is expected to be treated with respect and professionalism. Employment decisions are based solely on merit, qualifications, performance and capability.

Equal Employment and Opportunity Employer

Job Applicant Data Privacy Policy

Background Check

Any offer of employment is conditioned upon the candidate successfully passing a background check, which may include initial credit, motor vehicle record, public record, prior employment verification, and criminal background checks. Results of the background check are individually reviewed based upon legal requirements imposed by our regulators and with consideration of the nature and gravity of the background history and the job offered. Any offer of employment will include further information.


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