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Data Pipeline Jobs (NOW HIRING)

Data Engineer

Kansas City, MO ยท On-site

$111K - $134K/yr

Responsibilities : โ€ข Own MFour's consumer-data pipeline -- the core engine behind insights hundreds of leading brands rely on. โ€ข Solve a genuinely hard problem: unifying real-time app, web ...

Data Engineer

Kansas City, MO ยท On-site

$111K - $134K/yr

They are seeking a Senior Data Engineer to own the consumer-data pipeline, responsible for ingesting and unifying behavioral data into a reliable identity graph that supports their AI-driven ...

As the Data Manager, you'll own the pipeline from acquisition through preprocessing, lead the data operations team, and serve as the primary interface between the government and the contractor team ...

As the Data Manager, you'll own the pipeline from acquisition through preprocessing, lead the data operations team, and serve as the primary interface between the government and the contractor team ...

Data Engineer

Bellevue, WA ยท On-site

$129K - $155K/yr

Knowledge of Big Data pipelines, Data Engineering * Working Knowledge of the MSBI stack on Azure * Working Knowledge of Azure Data factory, Azure Data Lake, and Azure Data lake storage * Hands-on in ...

Data Engineer

Santa Clara, CA ยท On-site

$85K - $134K/yr

Construct and operate data pipelines: source connection, transformation logic, normalization rule implementation, DQ check configuration, and dashboard data feed maintenance; own the operational ...

Data Engineer

Irving, TX ยท On-site

$110K - $133K/yr

Design, develop, and maintain scalable data pipelines and ETL processes * Work extensively with MEM SQL (SingleStore) for real-time and large-scale data processing * Optimize database performance ...

Data Engineer

Tampa, FL ยท On-site

$108K - $129K/yr

Design, develop, and maintain scalable data pipelines and ETL processes * Work extensively with MEM SQL (SingleStore) for real-time and large-scale data processing * Optimize database performance ...

Data Engineer with Security Clearance

Reston, VA ยท On-site

$119K - $143K/yr

Monitor data pipeline performance and troubleshoot issues as needed * Collaborate with data analysts, data scientists, and software engineers to understand data needs * Ensure data quality, integrity ...

Data Engineer

Jackson, NJ ยท On-site

$116K - $140K/yr

Design, develop, and maintain scalable data pipelines and ETL processes * Work extensively with MEM SQL (SingleStore) for real-time and large-scale data processing * Optimize database performance ...

Data Engineer

NJ ยท On-site

$116K - $140K/yr

Design, develop, and maintain scalable data pipelines and ETL processes * Work extensively with MEM SQL (SingleStore) for real-time and large-scale data processing * Optimize database performance ...

Data Engineer, TS/SCI

Reston, VA

$119K - $143K/yr

S eeking a Lead Data Engineer / Mission Data Pipeline to serve as a Subject Matter Expert (SME). You will work directly with government, technical, and industry stakeholders design, implement, and ...

Data Engineer, TS/SCI

Reston, VA

$119K - $143K/yr

S eeking a Lead Data Engineer / Mission Data Pipeline to serve as a Subject Matter Expert (SME). You will work directly with government, technical, and industry stakeholders design, implement, and ...

Data Engineer, TS/SCI

Reston, VA ยท On-site

$119K - $143K/yr

S eeking a Lead Data Engineer / Mission Data Pipeline to serve as a Subject Matter Expert (SME).You will work directly with government, technical, and industry stakeholders design, implement, and ...

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Data Pipeline information

See salary details

$24K

$123.1K

$200K

How much do data pipeline jobs pay per year?

As of Jul 23, 2026, the average yearly pay for data pipeline in the United States is $123,131.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,000.00 and $155,500.00 per year, depending on experience, location, and employer.

What are some common challenges faced in Data Pipeline roles, and how are they addressed?

Professionals in Data Pipeline roles often encounter challenges such as handling large volumes of rapidly changing data, ensuring data quality, and minimizing downtime during data transfers. Addressing these issues typically involves implementing robust error-handling processes, automating data validation steps, and using scalable, resilient technologies. Collaboration with data analysts, software engineers, and business stakeholders is key to ensuring that pipelines meet organizational needs and remain flexible with evolving requirements. Continuous learning and adapting to new tools or frameworks also help Data Pipeline engineers stay ahead in this dynamic field.

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

To excel in a Data Pipeline role, you need strong skills in data engineering, programming (often Python, Java, or Scala), and experience with ETL (Extract, Transform, Load) processes, usually supported by a degree in computer science or a related field. Familiarity with technologies such as Apache Spark, Hadoop, Airflow, Kafka, and cloud platforms like AWS or GCP, along with relevant data engineering certifications, is highly valuable. Strong problem-solving abilities, attention to detail, and effective communication skills are critical for success in this position. These technical and interpersonal skills are essential for building, maintaining, and optimizing reliable data workflows that support business decision-making.

What engineer makes $500,000 a year?

Senior data engineers with extensive experience, advanced skills in cloud platforms, and expertise in building large-scale data pipelines can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within top tech companies. Achieving this level often requires strong technical certifications, leadership roles, and a track record of managing complex data infrastructure.

What does a Data Pipeline job involve?

A Data Pipeline job involves designing, building, and maintaining systems that automate the flow of data from various sources to storage and processing destinations. It includes extracting data from databases, APIs, or streaming sources, transforming it into the desired format, and loading it into data warehouses, lakes, or analytics platforms. The role requires expertise in data engineering, ETL (Extract, Transform, Load) processes, cloud computing, and workflow orchestration tools. Strong knowledge of programming languages like Python or SQL and experience with frameworks like Apache Airflow or Spark is often essential. The goal is to ensure data is efficiently collected, processed, and made available for analysis and decision-making.

What does a data pipeline do?

A data pipeline is a series of processes that automate the movement, transformation, and storage of data from source systems to destinations like data warehouses or analytics tools. Data pipeline roles often involve working with tools such as Apache Airflow, SQL, and cloud platforms to ensure data flows efficiently and accurately for analysis and reporting.

How to get hired on the pipeline?

To get hired as a data pipeline professional, candidates should have strong skills in data engineering, familiarity with tools like Apache Airflow, Spark, or Kafka, and experience with cloud platforms such as AWS or Azure. Relevant certifications and a solid understanding of data architecture can improve job prospects. Building a portfolio of projects and demonstrating problem-solving abilities are also beneficial.

Can I make 200K as a Data Engineer?

Data Engineers can earn $200,000 or more annually, especially with experience, advanced skills in cloud platforms, big data tools, and certifications. Salaries vary by location, industry, and company size, with senior roles and specialized expertise commanding higher pay.
More about Data Pipeline jobs
What cities are hiring for Data Pipeline jobs? Cities with the most Data Pipeline job openings:
What are the most commonly searched types of Data Pipeline jobs? The most popular types of Data Pipeline jobs are:
What states have the most Data Pipeline jobs? States with the most job openings for Data Pipeline jobs include:
Infographic showing various Data Pipeline 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 $123,131 per year, or $59.2 per hour.

Data Engineer

MFour Data Research

Kansas City, MO โ€ข On-site

$111K - $134K/yr

Full-time

This job post hasย expired 1 day ago.ย Applications are no longer accepted.


Job description

Job Summary:
MFour is a leading consumer intelligence platform transforming how businesses understand consumers. They are seeking a Senior Data Engineer to own the technical core of their consumer-data pipeline, responsible for ingesting, cleaning, and unifying behavioral data into a reliable identity graph.
Responsibilities:
โ€ข Own MFour's consumer-data pipeline โ€” the core engine behind insights hundreds of leading brands rely on.
โ€ข Solve a genuinely hard problem: unifying real-time app, web, purchase, ChatGPT, and foot-traffic data into one coherent identity graph.
โ€ข Sit at the center of the platform โ€” your pipeline feeds DANI's AI query layer and every customer-facing product.
โ€ข Build something that compounds: every improvement makes DANI smarter and every downstream team faster.
โ€ข Work directly alongside the Principal Platform Engineer and across all product teams.
โ€ข Own the end-to-end, multi-source pipeline: ingest, transformation, cleaning, and delivery.
โ€ข Enforce data-quality standards at ingest โ€” catch schema drift, anomalies, and source failures before they hit downstream systems.
โ€ข Keep the pipeline fast, scalable, and reliable for a live AI query layer, owning SLAs when upstream sources change.
โ€ข Own the identity-resolution system that merges behavioral signals into a clean, deduplicated identity graph โ€” the foundation DANI queries against.
โ€ข Build and refine entity-matching, dedup, and merge logic that resolves conflicting signals, with clear confidence rules.
โ€ข Partner with the Principal Platform Engineer to optimize data structures and access patterns for DANI โ€” low-latency, high-fidelity, queryable.
โ€ข Provide freshness and availability guarantees for Survey and Research fulfillment, backed by defined data contracts.
โ€ข Build monitoring and alerting across the pipeline (freshness, volume anomalies, schema violations, identity drift) so issues surface in minutes, not days.
โ€ข Own root-cause analysis for incidents โ€” trace failures to the source, document the fix, and harden against recurrence.
โ€ข Proactively retire technical debt before it becomes a risk.
โ€ข Enforce data-handling practices that keep behavioral data compliant with MFour's privacy commitments and applicable regulations.
โ€ข Maintain clear data lineage and retention policies that satisfy internal audits and enterprise-client trust.
โ€ข Deliver data to Survey and Research fulfillment teams that's available, correctly structured, and on time โ€” with clear ownership when it's not.
โ€ข Partner with the Product Pod to surface data constraints that shape what DANI can confidently answer.
โ€ข Document architecture, data contracts, and known failure modes so system knowledge isn't trapped in one person's head.
Qualifications:
Required:
โ€ข 5+ years of data engineering experience with clear ownership of production pipelines โ€” not just contribution to them. You have shipped and operated multi-source data systems at scale.
โ€ข Deep expertise in batch and streaming data pipeline architectures โ€” ingest, transformation, deduplication, and delivery โ€” using tools such as Apache Spark, Kafka, Flink, dbt, Airflow, or equivalents.
โ€ข Hands-on experience with entity resolution, identity matching, or record linkage across multiple data sources โ€” including the hard cases: conflicting signals, sparse data, and evolving schemas.
โ€ข Strong command of SQL and at least one general-purpose language (Python strongly preferred) for pipeline development, data validation, and operational tooling.
โ€ข Cloud data platform experience (AWS or GCP), including managed warehouses (Databricks and Snowflake), object storage, and cloud-native orchestration services.
โ€ข A rigorous approach to data quality: you define what 'clean' means, you build validation into the pipeline, and you treat a silent data error as seriously as a system outage.
โ€ข Familiarity with consumer data privacy requirements (CCPA, CPRA) and the practical implications for how behavioral data is collected, stored, and processed in a commercial research context.
Company:
Delivering validated consumer intelligence that brands can trust. Founded in 2001, the company is headquartered in Irvine, USA, with a team of 51-200 employees. The company is currently Growth Stage.