Data Analyst/CDP Developer (SQL/CDP Integration) Location: Torrance, CA (Hybrid of 4 days/week onsite along with 1 day/remote) Contract Duration - March 2026 - March 31, 2028 As a Data Analyst / CDP ...
Data Analyst/CDP Developer (SQL/CDP Integration) Location: Torrance, CA (Hybrid of 4 days/week onsite along with 1 day/remote) Contract Duration - March 2026 - March 31, 2028 As a Data Analyst / CDP ...
We are seeking a Microsoft SQL Database Developer and Business Intelligence Analyst with strong experience in healthcare, Medicare, or health insurance data. This role will design and manage our SQL ...
We are seeking a Microsoft SQL Database Developer and Business Intelligence Analyst with strong experience in healthcare, Medicare, or health insurance data. This role will design and manage our SQL ...
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Evening Sql Data Analyst information
See salary details
$34K - $43.3K
4% of jobs
$43.3K - $52.5K
7% of jobs
$52.5K - $61.8K
13% of jobs
$62.4K is the 25th percentile. Wages below this are outliers.
$61.8K - $71.1K
18% of jobs
The median wage is $75.4K / yr.
$71.1K - $80.4K
16% of jobs
$80.4K - $89.6K
13% of jobs
$93.1K is the 75th percentile. Wages above this are outliers.
$89.6K - $98.9K
9% of jobs
$98.9K - $108.2K
5% of jobs
$108.2K - $117.5K
9% of jobs
$117.5K - $126.7K
3% of jobs
$126.7K - $136K
2% of jobs
$34K
$82.6K
$136K
How much do evening sql data analyst jobs pay per year?
What are common challenges faced by evening SQL data analysts, and how can they be managed?
What is an evening SQL data analyst?
What skills and qualifications are needed to thrive as an evening SQL data analyst?
Do data analysts still use SQL?
Can an Evening Sql Data Analyst work at night?
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Re-posted 12 days ago
Job description
Data Analyst/CDP Developer (SQL/CDP Integration)
Location: Torrance, CA (Hybrid of 4 days/week onsite along with 1 day/remote)
Contract Duration โ March 2026 โ March 31, 2028
As a Data Analyst / CDP Developer, this person will support the customer data platform, improve data quality, implement scalable data solutions, and address end to end data challenges. This role requires advanced SQL development, CDP integration, pipeline operations, and troubleshooting across large scale datasets. The ideal candidate is highly analytical, detail oriented, and thrives in a fast paced, cross functional environment.
Responsibilities will include the following:
Data Analysis and Development
- Analyze customer data, event, and large-scale datasets to generate insights, validate data quality, and support business decision-making.
- Write, optimize, and maintain advanced SQL queries across Presto, Hive, and NoSQL systems.
- Use Python to support data processing, automation, workflow operations, and API integrations.
- Work within cloud platforms (primarily AWS) and apply general cloud data architecture principles.
- Perform exploratory data analysis to validate assumptions, identify anomalies, and support stakeholder requirements.
- Document data processes, business rules, logic, and workflows in Confluence or similar platforms.
- Collaborate with engineering, analytics, marketing, CRM teams, and SMEs to define data requirements and ensure accuracy.
- Operate CDP workflow orchestration tools (e.g., Digdag, TD Workflows) to manage pipelines and scheduled jobs.
- Enhance and monitor data quality frameworks including validation checks, alerts, and pipeline observability.
- Follow CI/CD and Git-based version control best practices for SQL, scripts, and documentation.
- Ensure adherence to privacy and compliance standards (GDPR, CCPA, PII).
- Solve end-to-end data challengesโfrom ingestion through transformation to analysis and activation.
- Maintain rigorous attention to detail, especially with customer-level and production data.
- Proactively improve automation, data quality, workflow reliability, and system performance.
- Communicate insights and technical concepts clearly to both technical and non-technical audiences.
- Partner with SMEs to understand business context, refine requirements, and validate solution accuracy.
Troubleshooting & Support:
- Diagnose and resolve data pipeline failures, ingestion issues, and workflow errors in a timely manner.
- Perform root cause analysis using logs, pipeline metadata, and system monitoring tools.
- Support production environments by monitoring scheduled jobs, validating outputs, and ensuring data accuracy and availability.
- Implement fixes, patches, and process improvements to prevent recurring problems.
- Maintain clear documentation of issues, resolutions, and preventive actions to strengthen operational reliability.
Required Skills and Expertise:
- Bachelor''s degree in Data Science, Computer Science, Information Systems, Engineering, or a related field.
- 5+ years of combined experience across data analysis, data engineering, or data operations.
- Advanced SQL and Query Optimization (Presto, Hive, NoSQL)
- Expertise in writing complex SQL queries optimizing them for large-scale datasets.
- Experience with Customer Data Platforms (CDP) and CRM Systems
- Hands-on experience integrating and managing CDP solutions and CRM platforms to unify and activate customer data.
- Strong SQL expertise, including complex joins, window functions, CTEs, performance optimization.
- Proficiency with Python for data processing, automation, and APIs.
- Experience working with customer data, event data, and large-scale datasets.
- Familiarity with cloud environments such as AWS, Google Cloud Platform, or Azure (S3, IAM, data storage concepts).
- Ability to perform exploratory analysis, validate data quality, and present insights to stakeholders.
- Understanding of data modeling, schema design, identity resolution, and profile unification.
- Comfortable documenting processes, transformations, and analytical logic in Confluence or similar platforms.
- Strong communication skills and the ability to work with cross-functional teams
- Hands-on experience with Treasure Data CDP or similar CDPs (Informatica, Adobe, Salesforce, mParticle, Tealium).
- Experience with workflow orchestration tools (Digdag, TD Workflows).
- Experience with data quality frameworks, monitoring, alerting, and pipeline observability.
- Experience with CI/CD, Git, and version control best practices.
- Understanding of privacy and compliance (GDPR, CCPA, PII handling).
- Skilled in providing support to a production environment.
- Strong problem-solving skills and the ability to deliver end-to-end solutionsโfrom data ingestion to analysis.
- Excellent attention to detail, especially when working with customer-level and production data.
- Proactive mindset for improving data quality, automation, and system reliability.
- Ability to collaborate closely with Subject Matter Experts (SMEs) to understand domain context, validate requirements, and ensure the accuracy and alignment of data solutions.