Senior Level Big Data Analyst Jobs
Senior level big data analyst jobs place experienced professionals in charge of analytical strategy, end-to-end pipeline ownership, and the cross-functional teams that turn raw data into decisions. Openings are concentrated across Technology & Software, with a mix of on-site, remote, and hybrid settings, and employers like Esolvit, TikTok, and KTek Resourcing hiring at this level now.
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Role: Apache Spark / Big Data Administrator
Location: Berkley Heights, NJ (Onsite)
Job Description
- 10+ years solid experience with deploying, configuring, monitoring, and troubleshooting Apache Spark clusters and associated big data frameworks (such as Hadoop, Kafka, or cloud-based data platforms) to ensure high availability and performance.
- Focuses on cluster health, performance tuning, and production data pipelines.
- Technical Experience: Deep hands-on experience with Apache Spark architecture (Driver, Workers, Executors, RDDs/DataFrames) and cluster managers (YARN, Kubernetes, or Mesos).
- OS & Scripting: Strong proficiency in Linux/Unix administration and scripting languages (Bash, Python, or Scala).
- Ecosystem Knowledge: Familiarity with big data and streaming tools like Hadoop HDFS, Kafka, Hive, or monitoring suites (Splunk, Prometheus, Grafana).
- Debugging Skills: Strong analytical capabilities to inspect logs, thread dumps, and metrics under heavy production loads.
- Excellent coordination with stakeholders and communication skills.
Must have experience with below responsibilities
- Cluster Management: Install, configure, and maintain Apache Spark clusters and node infrastructure in production and staging environments.
- Performance & Monitoring: Monitor cluster health, resource utilization (CPU, memory), and execution logs using tools like Spark UI, Splunk, or Elastic. Identify bottlenecks and optimize job execution times.
- Troubleshooting: Diagnose and resolve out-of-memory errors, executor failures, shuffle issues, and node crashes in distributed workloads.
- Pipeline & Integration Support: Support data engineers and developers in managing Spark applications, streaming jobs, and integrations with message brokers like Kafka.
- Security & Access Control: Implement security principles, role-based access control, authentication, and data encryption across the cluster.
- Backup & Disaster Recovery: Execute backup, recovery, and failover plans for Spark applications, configurations, and critical data stores.
- Patching & Upgrades: Apply software patches, driver updates, and version upgrades with minimal disruption to ongoing production jobs.
Role: Apache Spark / Big Data Administrator
Location: Berkley Heights, NJ (Onsite)
Job Description
- 10+ years solid experience with deploying, configuring, monitoring, and troubleshooting Apache Spark clusters and associated big data frameworks (such as Hadoop, Kafka, or cloud-based data platforms) to ensure high availability and performance.
- Focuses on cluster health, performance tuning, and production data pipelines.
- Technical Experience: Deep hands-on experience with Apache Spark architecture (Driver, Workers, Executors, RDDs/DataFrames) and cluster managers (YARN, Kubernetes, or Mesos).
- OS & Scripting: Strong proficiency in Linux/Unix administration and scripting languages (Bash, Python, or Scala).
- Ecosystem Knowledge: Familiarity with big data and streaming tools like Hadoop HDFS, Kafka, Hive, or monitoring suites (Splunk, Prometheus, Grafana).
- Debugging Skills: Strong analytical capabilities to inspect logs, thread dumps, and metrics under heavy production loads.
- Excellent coordination with stakeholders and communication skills.
Must have experience with below responsibilities
- Cluster Management: Install, configure, and maintain Apache Spark clusters and node infrastructure in production and staging environments.
- Performance & Monitoring: Monitor cluster health, resource utilization (CPU, memory), and execution logs using tools like Spark UI, Splunk, or Elastic. Identify bottlenecks and optimize job execution times.
- Troubleshooting: Diagnose and resolve out-of-memory errors, executor failures, shuffle issues, and node crashes in distributed workloads.
- Pipeline & Integration Support: Support data engineers and developers in managing Spark applications, streaming jobs, and integrations with message brokers like Kafka.
- Security & Access Control: Implement security principles, role-based access control, authentication, and data encryption across the cluster.
- Backup & Disaster Recovery: Execute backup, recovery, and failover plans for Spark applications, configurations, and critical data stores.
- Patching & Upgrades: Apply software patches, driver updates, and version upgrades with minimal disruption to ongoing production jobs.
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Senior Level Big Data Analyst Jobs: Frequently Asked Questions
How do I get a senior level big data analyst job?
Employers at this level look for candidates who have owned large-scale data infrastructure projects, not just contributed to them. Demonstrating that you have driven measurable business outcomes, mentored junior analysts, and made architectural decisions independently will set you apart. Tailoring your resume to show scope of ownership, technical stack depth, and cross-team influence matters far more than credentials alone.
Which companies hire senior level big data analysts?
Companies hiring senior level big data analysts right now include Esolvit, TikTok, and KTek Resourcing, based on current listings on Migrate Mate as of November 2026. At this experience level, hiring tends to come from large enterprises with mature data platforms as well as growth-stage technology companies scaling their analytics infrastructure.
Are there remote senior level big data analyst jobs?
Yes, remote and hybrid options are well represented at this level. About 0% of senior level big data analyst openings are remote or hybrid as of November 2026, reflecting the demand for experienced professionals who can operate independently without on-site supervision. Fully on-site roles do exist, particularly in regulated industries or on embedded data teams.
What makes a big data analyst role senior level?
Senior level big data analyst roles are defined by ownership and scope rather than task execution. At this level, you are expected to design data architectures, set analytical standards, guide technical decisions across projects, and mentor less experienced team members. The work shifts from answering assigned questions to framing the right questions, leading stakeholder conversations, and delivering systems others rely on.
Which industries hire the most senior level big data analysts?
Senior Level big data analyst roles concentrate in Technology & Software, based on current listings on Migrate Mate as of November 2026. These sectors generate the data volume and analytical complexity that require experienced professionals who can build and govern large-scale systems rather than simply run queries.