Slash batch times, scale machine-learning pipelines, and cut AWS EMR bills by hiring a vetted Spark engineer who starts in less than two weeks.. Zero freelancers and outsourcing fluff —just top-tier devs ready to go.
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Srdjan
Senior Developer
Verified
Tailor-made tech recruitment from scratch to cater to your exact needs:
- We don’t just test for technical skills—we assess for collaboration, communication, and time-zone compatibility. Because the best developer is the one who fits your team.
- While others scrambled to go remote, we’ve been building high-performing distributed teams for over a decade. We know what works (and what doesn’t).
- We present your shortlist in under 7 days. No bloated processes, no endless interviews. And if you’re not happy, we replace for free.
- Retention & Culture Fit. All hires are full-time, remote-permanent, and deeply aligned with your values. We monitor engagement and provide insights to keep them motivated for the long haul.
Engineers who read physical plans, tune shuffle partitions, convert sort‑merge joins to broadcast/hash joins, and exploit AQE features in Spark 3+ to cut job runtimes by 40‑70 %.
Professionals who design efficient schemas, column‑prune with Catalyst, partition and bucket data, and master EXPLAIN ANALYZE to eliminate full scans.
Apache Spark talent that builds exactly‑once, end‑to‑end pipelines with watermarking, windowed aggregations, and stateful operations for sub‑second
Developers fluent in both the Python and Scala/Java APIs, able to choose the right language for UDF performance and seamless integration with existing codebases.
Specialists who enforce ACID transactions, time‑travel, and scalable metadata with Delta Lake on Databricks or open‑source deployments.
Architects who migrate workloads from YARN to Kubernetes, configure dynamic allocation, and set executor/driver resources for cost‑efficient autoscaling.
Engineers who integrate Spark with Airflow, Prefect, or native job schedulers, leverage dynamic resource allocation, and manage SLA‑driven DAGs.
Experts who build large‑scale graph analytics (community detection, PageRank) for use‑cases like fraud detection and social‑network insights.
Practitioners who create end‑to‑end ML pipelines, tune models with cross‑validation on distributed data, and export them for real‑time inference.
When seeking out only the most qualified engineers for the Spark role, it‘s crucial for you to take a hands–on approach to the hiring process. It’s not just about technical skills but also about finding someone who fits with your company culture. We can help you with that.
As soon as you talk with us or fill out our form, the first thing we do is analyze your company. We set up a call with you to understand your culture and the type of people you value working with. Here’s how:
We reach out to hundreds of candidates that we think might be a possible match for you. In 2 weeks, you’ll start reviewing people that match your requirements. We focus on providing you 3-5 top candidates instead of giving you an endless list.
Once you select the candidate, we handle all the contracts and payments from day 1. We also take the legal steps required to protect your IP.
Below are the core Apache Spark solution areas our headhunted engineers deliver end‑to‑end for clients, covering batch, streaming, ML, lakehouse, and cloud operations.
| Real‑Time Streaming Analytics | Build exactly‑once pipelines with Structured Streaming, watermarking, and windowed aggregations for sub‑second dashboards and alerts |
| High‑Throughput Batch & ETL | Replace legacy MapReduce jobs with Spark SQL/DataFrame ETL that finishes 10–40× faster thanks to in‑memory processing |
| Lakehouse Architectures (Delta Lake / Hudi / Iceberg) | Combine data‑lake scale with warehouse ACID guarantees—time‑travel, schema evolution, and instant CDC merges |
| Machine‑Learning Pipelines (MLlib) | Distributed feature engineering, hyper‑parameter tuning, and model serving on petabyte‑scale data |
| Graph Analytics (GraphX / GraphFrames) | Large‑scale PageRank, community detection, and fraud‑graph traversals that don’t fit in single‑node graph databases |
| Interactive BI & Ad‑Hoc SQL | Spark SQL with adaptive query execution (AQE) powers interactive notebooks and BI tools, slashing query latency |
| Cost‑Optimized Cloud Clusters | Auto‑scaling Spark on AWS EMR, Google Dataproc, Databricks, or Kubernetes with dynamic allocation and spot‑instance savings |
| End‑to‑End Orchestration | Integrations with Airflow, Prefect, and native schedulers to manage SLA‑driven DAGs across batch and streaming workloads |
| Production Monitoring & Observability | Aggregated Spark metrics, event‑log analysis, and Prometheus/Grafana dashboards for performance, drift, and cost governance |
| Performance Tuning & Advisory | Catalyst plan analysis, shuffle partition tuning, broadcast joins, and AQE features that cut job runtimes by up to 70 % |
By hiring in countries with lower costs of living, your budget will stretch farther, while your remote Spark engineer will earn exactly what they want.
The best people already have jobs. We find senior big-data developers only working in established companies and bring them to your team.
Within two weeks of our discovery call, you’ll see 3-5 CVs of outstanding people. 80% of our clients hire from that first batch.
The candidates you’ll interview will have been chosen to match your company’s culture and values. They’ll feel right at home, reducing your turnover.
No freelancers, no consultants, no outsourcing. Only full-time Spark employees.
Hire career-driven developers ready to be part of your company.
Rest easy knowing your hires are well cared for. Our HR service handles global contract payments for you and provides social-emotional support to keep them performing at their best.
Get matched with your ideal developer—pre-vetted, timezone-aligned, and ready to code.
When you partner with DistantJob for your next hire, you get the highest quality developers who will deliver expert work on time. We headhunt developers globally; that means you can expect candidates within two weeks or less and at a great value.
Increase your development output within the next 30 days without sacrificing quality.
