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Data Engineer Jobs in Manchester, MD (NOW HIRING)

Orrstown Bank

Data Engineering Team Leader

Towson, MD · On-site

$150 - $200/hr

Data Engineering Team Leader Regular - Full time Management Harrisburg, PA, US 23 days ago Requisition ID: 2893 Position Summary: The Data Engineering Team Leader is responsible for innovating ...

Syntricate Technologies

Data Analytics Engineer

Towson, MD · On-site

$109K - $131K/yr

Syntricate Technologies is seeking a Data Analytics Engineer to join their team. The role involves working with Azure Data Factory and Microsoft Power Platforms to develop analytical reports and ...

Georgia IT, Inc.

Kafka Engineer

Owings Mills, MD · On-site

The role involves supporting the Kafka platform's engineering lifecycle, troubleshooting incidents, and collaborating with cross-functional teams to design scalable data solutions. Responsibilities ...

First Soft Solutions

Sr Kafka Developer

Owings Mills, MD · On-site

$50.50 - $65.50/hr

Job title KAFKA Developer Job summary: * Create Kafka SDS document and Kafka flow diagrams ... Develop Kafka Producer Microservices to publish the data to topics. * Develop stream processing ...

ClifyX

Data Architect

Hunt Valley, MD · On-site

$60.50 - $77.75/hr

Required : • Data modeling/Data Architecture 2-3 years should be good. more is bonus. • Good SQL knowledge. • worked on any programming language like java, python, pl-sql, hands on currently or ...

ClifyX

Data Architect

Hunt Valley, MD · On-site

$60.50 - $77.75/hr

Required : • Data modeling/Data Architecture 2-3 years should be good. more is bonus. • Good SQL knowledge. • worked on any programming language like java, python, pl-sql, hands on currently or ...

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Showing results 21-40

All JobsData Engineer JobsData Engineer Jobs in Manchester, MD

Data Engineer information

See Manchester, MD salary details

$42.3K

$123.3K

$168.7K

How much do data engineer jobs pay per year?

As of Sep 7, 2026, the average yearly pay for data engineer in Manchester, MD is $123,267.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,800.00 and $130,700.00 per year, depending on experience, location, and employer.

What is a data engineer?

Data Engineers are IT professionals who design, construct, install, and maintain large-scale processing systems and other infrastructure for collecting, storing, and analyzing data. They build and optimize data pipelines and architectures that allow organizations to efficiently access and use data for business insights. Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure that data is reliable, accessible, and secure. Their responsibilities often include working with databases, cloud platforms, and big data tools.

What are the key skills and qualifications needed to thrive as a data engineer, and why are they important?

To thrive as a Data Engineer, you need a strong background in computer science, data modeling, and programming languages such as Python or Java, often coupled with a relevant degree. Familiarity with ETL tools, big data frameworks (like Hadoop or Spark), and cloud platforms (such as AWS or Azure) is typically required, along with certifications like AWS Certified Data Analytics. Strong problem-solving skills, attention to detail, and effective communication set exceptional data engineers apart. These skills and qualities are essential for building robust data pipelines, ensuring data quality, and supporting data-driven decision-making across organizations.

What does a data engineer do?

The job duties of a data engineer involve helping with the development of systems, software, and infrastructure used to process, store and analyze data. Your responsibilities in this career include working to install data management software. Your employer may expect you to perform maintenance and install updates to all software and systems that they use for data acquisition, management, and analysis. Data engineers also analyze existing data systems to find ways to improve efficiency and accessibility. You then suggest upgrades or changes based on your assessment.

How do data engineers typically collaborate with data scientists and analysts within an organization?

Data Engineers play a crucial role in ensuring that Data Scientists and Analysts have reliable, well-structured data for their projects. This collaboration often involves building and maintaining data pipelines, optimizing data storage solutions, and troubleshooting data quality issues. Regular communication and agile teamwork are common, with Data Engineers frequently participating in meetings to understand analytical requirements and adjust data processes accordingly. By working closely together, these teams can quickly iterate on data models and deliver actionable insights to drive business decisions.

What is the difference between Data Engineer vs Data Scientist?

AspectData EngineerData Scientist
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
SkillsSQL, ETL, programming (Python, Java), database managementStatistics, machine learning, data analysis, programming (Python, R)
Work EnvironmentData warehouses, cloud platforms, backend systemsData analysis environments, research labs, visualization tools
Common ToolsApache Spark, Hadoop, Airflow, SQLJupyter, RStudio, Tableau, scikit-learn

Data Engineers focus on creating and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. Data Scientists analyze this data to generate insights, build predictive models, and support decision-making. While their skills overlap, Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior-level role that requires experience with programming, databases, and data pipeline tools. Entry-level positions may be available for those with relevant internships or strong foundational skills, but most data engineering roles demand several years of experience or advanced knowledge of tools like SQL, Python, and cloud platforms.

What is the role of a data engineer?

A data engineer designs, builds, and maintains data pipelines and infrastructure to collect, process, and store large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible and reliable for analysis and decision-making.
More about Data Engineer jobs

What are the most commonly searched types of Data Engineer jobs in Manchester, MD?

The most popular types of Data Engineer jobs in Manchester, MD are:

What are popular job titles related to Data Engineer jobs in Manchester, MD?

For Data Engineer jobs in Manchester, MD, the most frequently searched job titles are:

What cities near Manchester, MD are hiring for Data Engineer jobs?

Cities near Manchester, MD with the most Data Engineer job openings:

Data Engineer jobs near you
Infographic showing various Data Engineer job openings in Manchester, MD as of August 2026, with employment types broken down into 84% Full Time, 7% Temporary, and 9% Contract. Highlights an 78% In-person, 7% Hybrid, and 15% Remote job distribution, with an average salary of $123,267 per year, or $59.3 per hour.

Data Engineering Team Leader

Orrstown Bank

Towson, MD • On-site

$150 - $200/hr

Other

Re-posted 2 days ago

Job description

If you are unable to complete this application due to a disability, contact this employer to ask for an accommodation or an alternative application process.

Data Engineering Team Leader

Regular - Full time Management Harrisburg, PA, US

23 days ago Requisition ID: 2893

Position Summary:

The Data Engineering Team Leader is responsible for innovating, operating, influencing, and delivering systems architectures in support of our business. This position helps shape the technology strategy and alignment with corporate strategic goals. Responsibilities include (1) managing all aspects of system design, deployment, maintenance, and support for all systems within area of responsibility, (2) recruit, retain, and develop an exceptional systems engineering team, (3) create and refine operational processes to ensure effective security and compliance, (4) strengthen user experiences, service levels, and business relationships. The Data Engineering Team Leader will provide technical leadership, collaborate with cross-functional teams, and drive innovation in data engineering practices to support the bank's strategic objectives.

Qualifications:

  • Bachelor's degree in Computer Science, Information Systems, or a related field. A master's degree is preferred.
  • Minimum of seven years of systems engineering experience, with a focus on designing and implementing complex data solutions, preferably in the banking or financial industry.
  • Strong proficiency in SQL and experience with various relational databases (e.g., Oracle, SQL Server, MySQL) and related technologies.
  • Expertise in programming languages such as Python, Java, or Scala.
  • Solid understanding of data engineering concepts, techniques, and best practices.
  • Experience with big data technologies such as Hadoop, Spark, or similar frameworks.
  • In-depth knowledge of data integration, ETL processes, and data transformation techniques.
  • Proficiency in data modeling and database design principles.
  • Strong familiarity with cloud platforms like AWS, Azure, or Google Cloud, including relevant data services (e.g., Snowflake, Redshift, BigQuery).
  • Deep understanding of data governance, data quality, and data security practices, including regulatory compliance requirements.
  • Experience with data pipeline orchestration tools (e.g., Apache Airflow, Azure Data Factory, Qlik Talend)
  • Strong problem-solving and analytical skills.
  • Excellent communication and collaboration skills.
  • Ability to lead and mentor a team of data engineers.
  • Strong organizational and project management abilities.
  • Ability to adapt to changing technologies and work effectively in a dynamic environment.
  • Maintains high standards of personal integrity and accountability

Core Competencies:

Career Development: Proactively prepares and actively participates in ongoing, candid, constructive monthly Coaching sessions with supervisor. Seeks advancement into challenging and developmental roles and assignments. Sets and meets clear, measurable goals.

Communicates Effectively: Demonstrates the ability to effectively communicate with all employees and clients, regardless of level. Communicates clearly, concisely, with candor and confidence. Writes, speaks and listens to disseminate and receive information effectively and accurately. Seeks to understand the viewpoints of others. Keeps others informed in a timely manner.

Focuses on the Client: Anticipates and identifies internal and external client needs. Takes action to meet and, where possible, exceed client expectations. Plans and organizes work effectively to facilitate responsiveness to client and meet deadlines.

Judgment: Demonstrates sound reasoning and well-balanced thinking. Balances the need for action with the need for analysis. Incorporates strategic thinking skills into practice by examining facts. Shows an ability to problem solve complex issues. Probes beyond symptoms to determine the underlying cause. Learns from and accepts responsibility from mistakes.

Teamwork: Demonstrates the ability to enhance the department and Orrstown Banks development through participation. Holds self and others accountable for exceeding departmental and corporate goals. Develops strong working relationships throughout the organization. Appropriately voices opinions, even if they are contrary to the consensus of the team. Initiates and develops positive working relationships with others in a way that builds bridges across boundaries and breaks down silos. Relates to others in an open and accepting manner that creates trust, respect and a collaborative environment.

  • Lead the design, development, and maintenance of the bank's data infrastructure, including data pipelines, databases, and data warehouses.
  • Architect and optimize ETL processes to ensure efficient extraction, transformation, and loading of data from diverse sources into the bank's data storage systems.
  • Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and design scalable data solutions that support advanced analytics and reporting needs.
  • Implement and enforce data governance policies, ensuring data quality, consistency, security, and compliance with regulatory requirements.
  • Perform advanced data modeling and database design activities, optimizing data structures for integration, storage, and retrieval.
  • Lead performance tuning and optimization efforts to enhance data engineering systems' scalability, reliability, and throughput.
  • Stay abreast of emerging technologies, industry trends, and best practices in data engineering, and make recommendations for their application within the bank's environment.
  • Provide technical leadership, guidance, and mentorship to junior data engineers, fostering a culture of continuous learning and professional development.
  • Collaborate with IT teams to ensure seamless integration of data engineering solutions with existing infrastructure and applications.
  • Document data engineering processes, workflows, configurations, and system architectures.

Physical Requirements:

Physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

While performing the duties of this job, the employee is regularly required to sit, use hands to finger, handle or feel, reach with hands and arms, and talk or hear. The employee is frequently required to stand and walk. The employee may occasionally lift and/or move up to 10 pounds. Ability to reach destinations within the Orrstown footprint at all times is required.Ability to work and report to the employer’s physical work location(s).

Work is performed in an office setting with little to moderate exposure to noise, heat, dust or other adverse factors. Working extended hours may be required as needed. The noise level in the work environment is usually quiet.

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