Mid Level Data And Analytics Jobs
Mid level data and analytics jobs go to analysts and engineers ready to own end-to-end projects, guide junior teammates, and shape data-driven decisions without constant oversight. Hiring runs across Investment & Asset Management, Consulting & Professional Services, and Accounting & Auditing, with a strong mix of remote and hybrid opportunities, and employers like Deloitte, 4P Consulting, and Amazon Web Services competing for professionals at this level now.
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Showing 5 of 50+ Mid Level Data And Analytics jobs
INTRODUCTION
Hi We have an urgent role of Senior Data & Analytics Engineer with P&C insurance. URGENT HIRE! Data & Analytics Engineer with P&C insurance Looking for a contract developer for 6 months - this role is on the analytics team – needs someone who can help build the data marts effectively.
LOCATION: NYC - 3 days on site downtown NYC (final onsite interview)
DURATION: It might get extended past 6 months
JOB SUMMARY: Client is looking for a highly skilled Senior Data & Analytics Engineer with a strong technical background and deep understanding of the P&C insurance Industry. This role is critical in designing and delivering scalable, high-performance data solutions that empower analytics, reporting, and strategic decision-making. The ideal candidate will have expertise in Microsoft T-SQL, Azure Synapse Analytics, Azure Data Factory (ADF) and Power BI semantic layer, along with a solid grasp of insurance data domains such as policy, claims, underwriting, and actuarial.
BASIC QUALIFICATIONS:
- Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related discipline.
- 5+ years of experience in data engineering, analytics, or BI roles.
- Strong hands-on experience with Microsoft T-SQL, Azure Synapse Analytics, Power BI Semantic Layer (or SSAS) and Azure Data Factory.
- Proficiency in Python/PySpark. Experience with DAX is a strong plus.
- Experience with Git, branch management, and CI/CD pipelines in a data environment.
- Deep understanding of P&C insurance industry data (e.g., policy administration, claims processing, underwriting, actuarial models, ceded reinsurance).
- Working knowledge of insurance enterprise data models such as ACORD, IBM, etc.
- Experience with data warehousing, dimensional modeling, and data architecture.
- Proven ability to optimize performance in large-scale data environments.
- Excellent communication and collaboration skills with both technical and business stakeholders.
- Ability to manage concurrent deliverables in a fast-paced environment.
INTRODUCTION
Hi We have an urgent role of Senior Data & Analytics Engineer with P&C insurance. URGENT HIRE! Data & Analytics Engineer with P&C insurance Looking for a contract developer for 6 months - this role is on the analytics team – needs someone who can help build the data marts effectively.
LOCATION: NYC - 3 days on site downtown NYC (final onsite interview)
DURATION: It might get extended past 6 months
JOB SUMMARY: Client is looking for a highly skilled Senior Data & Analytics Engineer with a strong technical background and deep understanding of the P&C insurance Industry. This role is critical in designing and delivering scalable, high-performance data solutions that empower analytics, reporting, and strategic decision-making. The ideal candidate will have expertise in Microsoft T-SQL, Azure Synapse Analytics, Azure Data Factory (ADF) and Power BI semantic layer, along with a solid grasp of insurance data domains such as policy, claims, underwriting, and actuarial.
BASIC QUALIFICATIONS:
- Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related discipline.
- 5+ years of experience in data engineering, analytics, or BI roles.
- Strong hands-on experience with Microsoft T-SQL, Azure Synapse Analytics, Power BI Semantic Layer (or SSAS) and Azure Data Factory.
- Proficiency in Python/PySpark. Experience with DAX is a strong plus.
- Experience with Git, branch management, and CI/CD pipelines in a data environment.
- Deep understanding of P&C insurance industry data (e.g., policy administration, claims processing, underwriting, actuarial models, ceded reinsurance).
- Working knowledge of insurance enterprise data models such as ACORD, IBM, etc.
- Experience with data warehousing, dimensional modeling, and data architecture.
- Proven ability to optimize performance in large-scale data environments.
- Excellent communication and collaboration skills with both technical and business stakeholders.
- Ability to manage concurrent deliverables in a fast-paced environment.
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Find JobsMid Level Data And Analytics Job Market
Who's Hiring
- Deloitte20
- 4P Consulting4
- Amazon Web Services2
- City of Philadelphia2
- EXL1
Top Industries Hiring
- Investment & Asset Management20
- Consulting & Professional Services20
- Accounting & Auditing19
- Technology & Software9
- Distribution & Wholesale4
Mid Level Data And Analytics Jobs: Frequently Asked Questions
How do I get a mid level data and analytics job?
Position your experience around ownership and impact, not just task completion. Highlight projects where you drove a decision, built a pipeline from scratch, or improved a metric your team cared about. Tailor your resume to show depth in at least one domain, whether that is SQL, Python, visualization, or statistical modeling, and demonstrate you can work with minimal direction.
Which companies hire mid level data and analyticss?
Companies hiring mid level data and analytics professionals right now include Deloitte, 4P Consulting, and Amazon Web Services, based on current listings on Migrate Mate as of November 2026. Hiring at this level comes from a broad mix of employers, including technology firms, financial services companies, retailers, and healthcare organizations that rely on data teams to support product and business decisions.
Are there remote mid level data and analytics jobs?
Yes, and a meaningful share of openings offer flexible arrangements. About 16% of mid level data and analytics openings are remote or hybrid as of November 2026, reflecting strong employer demand for experienced professionals who can collaborate across distributed teams. On-site roles remain common in regulated industries and at companies building out in-person data culture.
How do I move up to a mid level data and analytics role?
Moving into a mid level role takes deliberate skill-building and demonstrated ownership over time. Focus on deepening technical skills in areas like data modeling, statistical analysis, or business intelligence tools, and look for opportunities to lead a project or mentor a peer. Employers want to see that you have delivered measurable results independently, not just supported others.
Which industries hire the most mid level data and analyticss?
Mid Level data and analytics roles concentrate in Investment & Asset Management, Consulting & Professional Services, and Accounting & Auditing, based on current listings on Migrate Mate as of November 2026. These sectors drive demand because they generate large volumes of data that require experienced analysts and engineers to translate into decisions around operations, customer behavior, risk, and product development.