Position at MTA Headquarters

JOB TITLE: Data Engineer Levels 1-3
DEPT/DIV: Chief Strategic Initiatives Officer/ Data & Analytics 
SUPERVISOR: Manager, Data Engineering 
LOCATION: 2 Broadway New York, NY 10004
HOURS OF WORK: 9:00 am - 5:30 pm (7 1/2 hours/day)
DEADLINE: Open Until Filled

Level 1: $67,172 - $88,163 | 406

Level 2: $75,484 - $99,073 | 496

Level 3: $82,411- $108,165 | 571

This position is eligible for telework which is currently one day per week. New hires are eligible to apply 30 days after their effective date of hire.

The MTA delivers subway, bus and commuter rail service and operates tolled bridges and tunnels in the New York City metro area. It is the largest public transportation provider in the Western Hemisphere, with millions of daily riders and a multi-billion-dollar budget. Delivering service and maintaining our infrastructure is increasingly data-driven, so data scientists are now central to the MTA’s operations and decision-making. As a member of the Data & Analytics team, you will work on a dynamic, growing team tasked with helping to define and achieve the MTA’s strategic priorities and address its most pressing challenges. Your work will become public data and influence critical decisions affecting millions of New Yorkers.

Our work combines new approaches and algorithms with a deep knowledge of our operations to deliver deeper insights into our performance. Our outputs are used by a wide array of stakeholders: from the MTA Board and senior execs to front-line managers to our open data customers. If you want to use your programming skills to solve complex problems and improve public transit in NYC, then we’d like to talk to you.
 
Data Engineers design, build, test, and deliver end-to-end, automated data pipelines over complex on-premises and off-premises platforms.They extract data from multiple source systems containing structured, semi-structured and unstructured data, refine it to make it consistent,
reliable, and available to colleagues on the Data & Analytics team, operations and management teams across the MTA, and, in support of the agency’s and New York State’s Open Data goals, to external stakeholders and the general public.

They will use languages such as SQL and Python and tools such as Oracle, Postgres, and SQL Server to analyze large datasets, build new ones, and design overall data architectures. They will carefully document all work and work closely with colleagues to define needs, problem-solve, support the overall team agenda, and build relationships throughout and at all levels of the agency. They will have to be able to quickly learn the unique features, data constraints and business needs of any part of the MTA. In addition, unlike other data engineering roles, they will support the entire downstream pipeline process and, occasionally, end-users of the data products. In general, they will have to support the MTA’s strategic goals to build data systems and processes that are well-structured and sustainable. 

All Data Engineers must be able to:
• Develop and operationalize data pipelines, data warehouses, data marts, multi-dimensional 
cubes, and data lakes to collect, structure, and integrate a wide range of data sources make 
information available to staff and decision-makers for analysis and consumption.
• Support the development of new data sets, data access, extraction methodologies, algorithms, 
and processes to improve performance.
• Help evaluate legacy data sources and implement plans for migration to modern data 
infrastructure to improve efficiency, timeliness, quality, robustness, and scalability.
• Test data sets and pipelines for data quality and usability, conducting root cause analyses in 
response to issues, and implement cost effective resolutions for data anomalies.
• Prepare data architecture diagrams and system documentation as well as summaries of business 
rules, data flow maps, and other design artifacts to ensure understanding of all users and 
audiences, both technical and non-technical.
• Provide input into data governance and sustainable data management policies and practices 
across the agency.
• Keep skills current and maintain data systems in the latest technologies and cloud platforms for 
collection, integration, ingest, transformation, and organization to support analyses, reporting, 
and all business needs.
• As assigned by the manager, carry out project workstreams, support project management, and 
communicate with teammates, clients and all relevant parties on project status.
• Support a professional environment that respects individual differences, enables all colleagues 
to develop and contribute to their full potential at the MTA and beyond.
• Perform other duties as assigned.

Level 2 Data Engineers must also be able to:
• Project manage new data pipeline development and legacy data system conversion to create 
data system assets that are efficient, timely, reliable and accurate, robust, and scalable.
• Develop new methodologies, algorithms, and scripts as needed for extraction, transformation, 
and quality assurance.
• Help develop standards and create actual data architecture diagrams, system documentation, 
data models, business decision-making maps, and other design related artifacts to ensure 
consistency and improve understanding of both technical and non-technical users of Data & 
Analytic products.
• Research and recommend the best pipeline technologies, toolsets, and applications to support 
the data science and reporting teams’ efforts.
• In consultation with managers in the Data & Analytics function, design workstreams and project 
plans, help carry out project management, update project plans as needed, and communicate 
with clients and all relevant parties on project status. Revise work plans when unplanned events 
occur, communicating updates and rationales to stakeholders and teammates.
• Support efforts to recruit new engineers and develop existing teammates. As requested by 
manager, review team member code for efficiency, clarity, and adherence to best practices.

Level 3 Data Engineers must also be able to:
• Operationalize data pipelines, data warehouses, data marts, multi-dimensional cubes, and data 
lakes. 
• Find solutions to project challenges using enterprise-class solutions.
• Lead project planning and support manager in overall work planning, team and client 
communications.
• Ensure data governance and sustainability needs are met in project designs and systems 
maintenance.
• Identify and propose new data-analysis projects that support the agency strategic goals, service 
quality and efficiency. Advance data-driven decision-making across the company through 
stakeholder partnering, tool design, and effective communications.
• Support the selection and development of teammates within the department. Mentor less-experienced members of the team to build their business and coding/analytic knowledge and 
skills.

All Data Engineers must have:
• Strong skills in software engineering, database designs, and data pipeline orchestration.
• Ability to work with structured, semi-structured, unstructured data from numerous disciplines, 
such as transportation, finance, HR, and asset maintenance.
• Experience with data engineering orchestration tools (e.g., Airflow) and DevOps tools (e.g., Git) 
and familiarity with related concepts.
• Ability to manage workstreams and work on team-based projects.
• Ability to think at a policy and strategic level.

• Strong written communication skills.

Level 2 Data Engineers must also have:
• Ability to collaborate with data scientists, data reporters, and end users on project design and 
business goals.
• Extensive experience working unstructured, as well as semi-structured and more structured 
data from a variety of policy areas— as well as from distinct disciplines — transportation, 
finance, HR, asset maintenance.
• Experience managing with the operating and organization constraints of the public management
sphere.
• Familiarity with common algorithms used to calculate KPIs and an understanding of how data 
are fed into data visualization/ business intelligence tools such as PowerBI.
• Experience in quality assurance techniques and automated testing practices.
• Knowledge of current innovations and techniques in data engineering.
• Ability to work with agency colleagues at all levels, from frontline managers to executives, who 
use data and data products for decision-making.
• Ability to project manage and help lead team-based projects.

Level 3 Data Engineers must also have:
• Ability to play a lead role on the Data & Analytics team to set priorities and overall program 
planning in support of business goals.
• Excellent judgment on how to manage or overcome technical, organizational, or governance 
constraints to meet business goals.
• Extensive experience with data visualization and/or business intelligence tools such as PowerBI.
• Extensive experience and ability to design and implement quality assurance and automated 
testing systems.
• Extensive experience in project design and management and the ability to lead successful team-based projects.
• Proactive interest in identifying strategic, policy, and business issues in all proposed and ongoing 
projects.
• Experience managing clients and stakeholders in all projects.

All Data Engineers must have:
• A bachelor's degree in Computer Science, Engineering, Information Management, Statistics, 
Mathematics, or an equivalent combination of education and experience. Master’s degree 
preferred.
• A minimum of (1) year of experience working in data engineering or a position with similar 
programing and data management content.
• A minimum of (1) year of experience building data pipelines, automating tasks through scripts, 
writing database queries and debugging/ maintaining code.
• A minimum of (2) years’ experience with Python and SQL programming.
• A minimum of (2) years’ experience with relational databases (e.g., Oracle, Postgres, SQL 
Server), including writing queries to obtain and manipulate data.

Level 2 Data Engineers must also have:
• At least (2) years’ experience working in a data engineering or a position with similar programing 
and data management content.
• A minimum of (2) years’ experience building pipelines, automating tasks through scripts, writing 
database queries and debugging/ maintaining code.
• A minimum of (3) years’ experience with Python and SQL programming.
• A minimum of (3) years’ experience with relational databases (e.g., Oracle, Postgres, SQL 
Server), including writing queries to obtain and manipulate data.

Level 3 Data Engineers must also have:
• At least (3) years’ experience working in a data engineering or a position with similar programing 
and data management content.
• A minimum of (3) years’ experience building pipelines, automating tasks through scripts, writing 
database queries and debugging/ maintaining code.
• A minimum of (4) years’ experience with Python and SQL programming.
• A minimum of (4) years’ experience with relational databases (e.g., Oracle, Postgres, SQL 
Server), including writing queries to obtain and manipulate data.

OTHER INFORMATION
Pursuant to the New York State Public Officers Law & the MTA Code of Ethics, all employees who hold a policymaking position must file an Annual Statement of Financial Disclosure (FDS) with the NYS Commission on Ethics and Lobbying in Government (the “Commission”).

EQUAL EMPLOYMENT OPPORTUNITY
MTA and its subsidiary and affiliated agencies are Equal Opportunity Employers, including with respect to veteran status and individuals with disabilities.

The MTA encourages qualified applicants from diverse backgrounds, experiences, and abilities, including military service members, to apply.