Big Data Analyst Jobs
Big Data Analyst jobs are open across technology, finance, healthcare, retail, and government, at every level from entry-level analyst to principal and staff, with specializations in data engineering pipelines, predictive modeling, and business intelligence. Scan the live roles below and apply to whichever ones fit.
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Job ID:
J54850
Job Title:
Big Data Platform Engineer
Location:
Chicago, IL
Duration:
8 Months + Extension
Domain Exposure:
Material
Client:
To Be Discussed Later
Employment Type:
W-2, 1099, C2C
Work Authorization:
US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other
Job Title: Big Data Platform Engineer
Location: Chicago,IL
Duration: 8 months
Bill Rate: $71/hour (C2C)
Job Type: W-2, 1099, C2C
Client: To Be Discussed Later
Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other
Job Description:
Seeking an experienced Spark, HDFS, and Kafka Administrator/Engineer to manage, support, and optimize enterprise-grade big data platforms. Deep hands-on expertise with Apache Spark, HDFS, and Kafka is required and will be the primary focus of this role. Experience administering these technologies within a Cloudera environment is preferred but secondary to strong expertise in the core underlying platforms.
Key Responsibilities:
- Spark Administration: Deploy, configure, monitor, tune, and troubleshoot Apache Spark environments and workloads. Support Spark job performance, resource management, capacity planning, and production operations.
- HDFS Administration: Manage and support HDFS storage, including capacity, performance, availability, permissions, replication, and troubleshooting. Ensure robust integration between distributed compute platforms and storage.
- Kafka Administration: Deploy, configure, manage, monitor, and troubleshoot Apache Kafka clusters, topics, producers, and consumers. Support performance, capacity, availability, security, and production operations.
- Monitoring & Performance Tuning: Monitor platform connectivity, health, capacity, and performance using tools such as Grafana, Splunk, and related management utilities. Proactively identify and resolve bottlenecks across Spark, HDFS, and Kafka.
- Security & Compliance: Implement and manage security configurations, including Kerberos, SSL/TLS, authorization policies, HDFS ACLs, and enterprise IAM/LDAP integrations.
- Automation & Scripting: Develop and maintain automation using Python, Bash, or Perl for routine administration, configuration management, monitoring, and operational support.
- Troubleshooting & Support: Provide expert-level troubleshooting and technical support across the big data tech stack, including participation in an on-call rotation.
- Platform Lifecycle: Support installations, patching, upgrades, migrations, and maintenance activities while minimizing downtime. Support Cloudera Hadoop/CDP administration as needed.
Qualifications & Requirements:
- Core Experience: Minimum 3–5 years of hands-on production administration, configuration, performance tuning, and sizing experience with Apache Spark, HDFS, and Apache Kafka.
- Linux Administration: Solid hands-on experience with Linux operating systems, logging in, navigating, and executing command-line administration.
- Monitoring & Observability: Practical experience using enterprise monitoring and operational tooling such as Grafana and Splunk.
- Security Foundations: Solid understanding of Kerberos authentication, SSL/TLS encryption, IAM/LDAP integration, and general security concepts for distributed data architectures.
- Communication & Collaboration: Excellent analytical, problem-solving, and written/verbal communication skills.
- Education: Bachelor’s degree in Computer Science, Information Systems, or a related field.
Preferred / Desirable:
- Experience with Cloudera Hadoop/CDP and Cloudera Manager (preferred, but secondary to foundational Spark, HDFS, and Kafka expertise).
- Cloudera certifications or equivalent big data
We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.
Big Data Analyst Jobs by Experience Level
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Find Big Data Analyst JobsBig Data Analyst Job Market
Who's Hiring



Top Industries Hiring
- Technology & Software12
- Education1
- Consulting & Professional Services1
What Employers Look For
The qualifications that appear most often in big data analyst jobs.
- Proficiency in SQL, Python, or Scala for large-scale data processing
- Hands-on experience with distributed computing frameworks such as Hadoop or Spark
- Familiarity with at least one major cloud data platform, AWS, GCP, or Azure
- Bachelor's degree in computer science, statistics, mathematics, or a related field
- Experience building or maintaining ETL and data pipeline workflows
- Ability to communicate analytical findings to non-technical stakeholders through visualization tools
Tips for Your Big Data Analyst Job Search
Tailor your resume to stack size
Hiring managers for big data analyst roles scan for specific tools before reading anything else. List your exact stack, Hadoop, Spark, Hive, Kafka, or cloud platforms, in a dedicated skills section near the top so it clears automated screening quickly.
Show scale in every project bullet
Vague bullets like 'analyzed large datasets' get skipped. Quantify the volume, row counts, pipeline frequency, or query runtime improvements. Reviewers need to judge whether your experience matches the data scale their team actually works at.
Filter openings by cloud platform first
Many big data analyst postings are written around a single cloud ecosystem, AWS, GCP, or Azure. Searching by platform alongside your job title cuts down irrelevant listings and surfaces roles where your existing certifications carry direct weight.
Apply early to roles that fit
Migrate Mate lists big data analyst openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare a SQL and Python live-coding answer
Most big data analyst technical screens include at least one live query or scripting problem. Practice writing window functions, aggregations, and DataFrame transformations without documentation open, because interviewers time these and judge both accuracy and speed.
Negotiate on scope, not just base pay
When you reach the offer stage, ask about data access, tooling budget, and whether the role owns production pipelines or only consumes them. Those factors affect your day-to-day growth more than a small salary difference does.
Big Data Analyst Jobs: Frequently Asked Questions
Which companies are hiring the most big data analysts?
The most active employers for big data analysts right now are TikTok, Esolvit, and KDA Consulting, and the most openings are in Virginia, California, and Texas, based on current listings on Migrate Mate as of November 2026. Financial services, healthcare, and large technology companies consistently post the highest volume of these roles.
How many big data analyst jobs are remote?
About 44% of big data analyst openings are fully remote or hybrid as of November 2026, reflecting strong demand for distributed data teams. Roles focused on pipeline engineering and cloud-based BI tend to be the most remote-friendly, while positions tied to on-premise data centers or regulated healthcare systems lean toward hybrid or on-site arrangements.
How do you become a big data analyst?
Start by building a foundation in SQL and Python, then learn a distributed processing framework like Spark or Hadoop through project work or coursework. Add cloud experience on a free-tier account, build a portfolio of end-to-end pipeline or modeling projects, and target entry-level data analyst or data engineering roles that expose you to production-scale datasets before moving into dedicated big data positions.
Can you get a big data analyst job with little experience?
Yes, employers do hire candidates without full-time big data experience when applicants demonstrate hands-on project work at scale. Build public GitHub projects that process real, large datasets, obtain a cloud data certification on a major platform, and target companies with structured data rotation programs or analyst development tracks, since those roles are designed to bring capable candidates up to production speed.
What does the big data analyst interview process look like?
Most big data analyst interviews run in three to four stages: an initial recruiter screen, a technical take-home or live-coding round covering SQL and Python, a system design or architecture discussion where you walk through how you'd build or improve a data pipeline, and a final panel with cross-functional stakeholders who assess communication and business judgment. Some employers also include a case study using a sample dataset.
Where can I find and apply to big data analyst jobs?
You can find and apply to big data analyst jobs on Migrate Mate, which lists current openings from employers across the United States. Search the listings to find roles that match your stack and experience level, then apply directly to each one that fits.
See All 54 Big Data Analyst Jobs
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