Sr Data Engineer Client information
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$89.5K - $98.1K
9% of jobs
$105.9K is the 25th percentile. Wages below this are outliers.
$98.1K - $106.6K
11% of jobs
$106.6K - $115.2K
13% of jobs
The median wage is $121.4K / yr.
$115.2K - $123.7K
16% of jobs
$123.7K - $132.3K
11% of jobs
$140K is the 75th percentile. Wages above this are outliers.
$132.3K - $140.8K
10% of jobs
$140.8K - $149.4K
9% of jobs
$149.4K - $157.9K
6% of jobs
$157.9K - $166.5K
5% of jobs
$166.5K - $175K
3% of jobs
How much do sr data engineer client jobs pay per year?
As of Aug 20, 2026, the average yearly pay for sr data engineer client in the United States is $126,328.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,000.00 and $144,000.00 per year, depending on experience, location, and employer.
Sr Data Engineer Client roles refer to senior-level data engineering positions that focus on building, managing, and optimizing data infrastructure and pipelines to serve client-facing applications or external customers. These professionals are responsible for designing scalable data solutions, integrating diverse data sources, and ensuring data quality and security. They often collaborate with data scientists, analysts, and client teams to deliver actionable insights and support business objectives. Strong technical skills in data modeling, ETL processes, and cloud platforms are essential, along with experience in stakeholder communication.
Sr Data Engineers working with client data often encounter challenges such as aligning disparate data formats, managing inconsistent data quality, and ensuring data security during integration. Effective communication with both client and internal teams is crucial to clearly understand requirements and address technical limitations. These challenges can be mitigated by establishing robust data pipelines, thorough documentation, and proactive collaboration with stakeholders throughout the integration process.
To thrive as a Sr Data Engineer Client, you need extensive experience in data engineering, strong proficiency in SQL, Python, and data modeling, often supported by a bachelor's or master's degree in computer science or a related field. Mastery of big data tools (like Hadoop or Spark), cloud platforms (such as AWS or Azure), and relevant certifications is highly valued. Exceptional problem-solving, communication, and stakeholder management skills help you bridge technical and business needs. These capabilities are crucial for delivering scalable data solutions that drive informed decision-making and client satisfaction.
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