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Freelance Data Pipeline Engineer Jobs (NOW HIRING)

Key Role Description The Pipeline Engineer sustains project management and integrity management for ... HCA) data, Environmental and many other inputs. * Assumes budgeting stewardship of OpEx/CapEx as ...

Key Role Description The Pipeline Engineer sustains project management and integrity management for ... HCA) data, Environmental and many other inputs. * Assumes budgeting stewardship of OpEx/CapEx as ...

About the Role This is a freelance role for a Tendem project. As a Python Data Scraping Engineer, you'll handle data scraping tasks requiring technical precision for web extraction and processing ...

Senior Pipeline Engineer

Pittsburgh, PA ยท On-site

$68K - $136K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Preparation of equipment specifications and data sheet creation * Development of field procedures ... Bachelor's Degree in Engineering or applied science "Mechanical Engineer, Civil Engineer, Pipeline ...

Job Title AI PIPELINE ENGINEER Location Huntsville, AL 35806 US (Primary) Category Engineering Job ... data ingestion, processing, and model deployment using frameworks like LangChain and Open WebUI ...

Senior Pipeline Engineer

Houston, TX ยท On-site

$99K - $137K/yr

Be our next Senior Pipeline Engineer! Your work environment at EXP In this role, you will be a part ... Will provide direction to junior/intermediate engineers to complete data analysis, drawing and ...

New

Senior Pipeline Engineer

Houston, TX ยท On-site

$99K - $137K/yr

Be our next Senior Pipeline Engineer! Your work environment at EXP In this role, you will be a part ... Will provide direction to junior/intermediate engineers to complete data analysis, drawing and ...

The Role As a Data Pipeline Intern, you'll work directly alongside our data and robotics engineering teams to support the infrastructure that feeds our foundation models. You'll get hands-on ...

Senior Pipeline Engineer

Houston, TX ยท On-site

$91K - $140K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Preparation of equipment specifications and data sheet creation. * Development of field procedures ... Bachelor's Degree in Engineering or applied science "Mechanical Engineer, Civil Engineer, Pipeline ...

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Freelance Data Pipeline Engineer information

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How much do freelance data pipeline engineer jobs pay per hour?

As of Aug 17, 2026, the average hourly pay for freelance data pipeline engineer in the United States is $47.71, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $61.78 per hour, depending on experience, location, and employer.

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

To thrive as a Freelance Data Pipeline Engineer, you need strong skills in data modeling, ETL development, and proficiency with programming languages like Python or Scala, typically supported by a degree in computer science or a related field. Familiarity with tools such as Apache Airflow, Spark, SQL databases, and cloud platforms like AWS or Google Cloud, along with relevant certifications, is often required. Excellent problem-solving, communication, and project management skills set outstanding freelancers apart in client-facing environments. These competencies ensure robust, scalable data pipelines that deliver reliable insights and meet diverse client requirements.

What does a freelance data pipeline engineer do?

A Freelance Data Pipeline Engineer is responsible for designing, building, and maintaining systems that move and process data efficiently between different sources and destinations. They work on extracting data from various sources, transforming it into usable formats, and loading it into databases or data warehouses. As freelancers, they work independently or on contract for different clients, adapting to various data environments and project requirements. Their work ensures that businesses have access to accurate, timely, and well-structured data for analytics and decision-making.

What are some common challenges faced by freelance data pipeline engineers when working with multiple clients?

Freelance Data Pipeline Engineers often navigate the challenge of adapting to diverse data architectures, tools, and workflows across different clients. Each organization may use unique cloud platforms, data storage solutions, and security protocols, requiring quick learning and flexibility. Additionally, managing communication and expectations remotely, especially when stakeholders are in different time zones, can be demanding. Successfully balancing multiple projects also requires strong organizational skills and the ability to prioritize tasks effectively.
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Infographic showing various Freelance Data Pipeline Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $99,230 per year, or $47.7 per hour.

Senior Vice President, Data Pipeline Engineer - Ontology & Investment Data Standard (IDS)

BNY

Pittsburgh, PA โ€ข On-site

$111K - $133K/yr

Full-time

Re-posted 2 days ago


Job description

hackajob is collaborating with BNY to connect them with exceptional professionals for this role.

Weโ€™re seeking a future team member for the role of Data Pipeline Engineer to join our Data Innovation team. In this role, you will design and build the data pipelines that power our Investment Data Standard (IDS) and knowledge graph, enabling a unified, high-quality data ecosystem that supports analytics, AI, and client-facing solutions. You will partner closely with the Ontology/Knowledge Architecture lead and collaborate across platform, product, and data teams to deliver scalable, production-ready solutions aligned to our broader data transformation strategy. This role is located in Pittsburgh, PA or Lake Mary, FL.

In this role, youโ€™ll make an impact in the following ways: 

  • Design and build scalable pipelines to ingest and process data from internal platforms and external vendors across batch, streaming, and near real-time patterns.
  • Transform diverse data formats (APIs, flat files, streaming, unstructured) into clean, standardized time-series and event-driven datasets aligned to IDS entity models.
  • Develop reusable frameworks to normalize identifiers, symbology, units, hierarchies, and event data (e.g., corporate actions, transactions).
  • Partner with Ontology/Knowledge architecture team to map source data to canonical entities, relationships, and attributes, enabling graph ingestion and entity resolution.
  • Implement robust data quality controls (completeness, accuracy, consistency, schema drift, anomaly detection) with full lineage, provenance, and traceability (source โ†’ IDS โ†’ product).
  • Enable multi-vendor data ingestion, comparison, and reconciliation, including source prioritization, hierarchy logic, and coverage/quality analytics.
  • Build modular, reusable, cloud-native pipelines optimized for scale, performance, and cost (e.g., Snowflake), with monitoring and SLA-driven reliability.
  • Collaborate cross-functionally to translate business and data requirements into production-ready pipelines and support downstream distribution via APIs, data products, and client platforms.

To be successful in this role, weโ€™re seeking the following: 

  • Bachelor's degree in a related discipline or equivalent work experience required. An advanced degree with a preference in statistics/statistical analysis is preferred.
  • At least six yearsโ€™ total work experience, with at least 3 yearsโ€™ experience with a strong focus on data analysis and business intelligence is preferred.
  • Extensive experience in data engineering, building and scaling production-grade data pipelines.
  • Deep hands-on expertise in Python, Spark, and SQL, with strong experience in ETL/ELT frameworks and orchestration tools.
  • Proven ability to design and operate high-volume, resilient pipelines across batch, streaming, and distributed environments.
  • Strong understanding of structured and semi-structured data modeling, including time-series and event-driven architectures.
  • Experience designing data transformation and normalization layers, including schema evolution and backward compatibility.
  • Expertise with modern data platforms (e.g., Snowflake, AWS, Databricks), lakehouse architectures, and API-based data integration.
  • Strong capabilities in performance tuning, cost optimization, and implementing data quality, monitoring, logging, and lineage frameworks.
  • Domain experience with financial datasets (market data, pricing, reference data, portfolio holdings, transactions, corporate actions) and familiarity with key vendors (e.g., Bloomberg, ICE, MSCI).
  • Exposure to knowledge graph/ontology-driven systems, entity resolution workflows, AI/LLM-based unstructured data integration (e.g., documents, PDFs), and data entitlements, licensing, and usage tracking is preferred.

At BNY, our culture allows us to run our company better and enables employeesโ€™ growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the worldโ€™s investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide.

Recognized as a top destination for innovators, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance โ€“ and this is what #LifeAtBNY is all about. Join us and be part of something extraordinary.