Hire Data Engineers
Hire Data Engineers Who Build Pipelines That Scale
Hire senior data engineers who design and build reliable data pipelines, warehouses, and analytics infrastructure. Our engineers integrate with your team or work within managed Pods—delivering production-ready data systems with proper testing and documentation.
Why Salt
Why Hire Data Engineers from Salt
When you hire data engineers through Salt, you get more than SQL skills on a resume. Our engineers are vetted for real-world expertise—building data systems that are reliable, scalable, and maintainable.
Pre-Vetted Specialists
Only 3% of applicants pass our screening. SQL proficiency tests, pipeline design exercises, and real-world scenario assessments.
Modern Data Stack Expertise
Not just legacy ETL. Our engineers know dbt, modern orchestrators, cloud-native warehouses, and lakehouse architectures.
Fast Onboarding
Start interviewing within days, not weeks. Our pre-vetted pool means you skip months of recruitment.
Risk-Free Trial
2-week trial with every hire. If it's not working, we replace at no extra cost. Your satisfaction guaranteed.
AI-Native Engineers
Our engineers leverage AI tools to write SQL, debug pipelines, and generate documentation faster—without sacrificing quality.
Outcome-Oriented
Not just pipeline builders—engineers who understand business context, optimize for cost, and build systems that scale.
Technical Expertise
Data Engineering Skills Our Engineers Bring
From pipeline orchestration to data modeling, our engineers have deep experience across the modern data stack.
Data Pipelines
- Apache Airflow
- Prefect & Dagster
- ETL/ELT Design
- Batch & Micro-batch
- Pipeline Orchestration
Data Warehousing
- Snowflake
- Google BigQuery
- Amazon Redshift
- Azure Synapse
- Data Modeling
Transformation & Modeling
- dbt (data build tool)
- Dimensional Modeling
- Data Vault 2.0
- Slowly Changing Dimensions
- Semantic Layers
Big Data & Processing
- Apache Spark
- Databricks
- PySpark & Spark SQL
- Delta Lake / Iceberg
- Distributed Computing
Streaming & Real-time
- Apache Kafka
- Spark Streaming
- Flink
- Event-Driven Architecture
- Real-time Analytics
Cloud & Infrastructure
- AWS (Glue, EMR, S3)
- GCP (Dataflow, BigQuery)
- Azure Data Factory
- Terraform / IaC
- Data Lake Architecture
Capabilities
What Our Data Engineers Deliver
Beyond writing SQL—our engineers own data infrastructure end-to-end and build production-ready systems.
Pipeline Architecture
Design and build reliable data pipelines that handle millions of records with proper error handling, retries, and monitoring. From batch to streaming.
Data Warehouse Design
Model data warehouses using best practices—star schemas, data vaults, or hybrid approaches. Optimize for query performance and cost efficiency.
Analytics Infrastructure
Build the foundation for analytics and BI teams. Semantic layers, data marts, and well-documented models that analysts can trust.
Data Quality & Governance
Implement data quality checks, lineage tracking, and governance frameworks. Ensure data accuracy, freshness, and compliance requirements.
ML-Ready Data
Prepare data for machine learning—feature stores, training datasets, and MLOps integration. Bridge the gap between data engineering and data science.
Team Integration
Participate fully in your development process including code reviews, architecture discussions, and collaboration with analysts and data scientists.
How to Hire Data Engineers
Hire Data Engineers in Weeks, Not Months
Our streamlined hiring process gets pre-vetted data engineers on your team fast. Skip the lengthy recruitment cycles.
Share Your Requirements
Tell us about your data infrastructure, tech stack (Snowflake, Databricks, etc.), and the experience level you need. We'll help you define the right profile.
Get Matched Profiles
We present 2-3 pre-vetted data engineers who match your requirements. Review their experience, pipeline samples, and our assessment notes.
Interview & Select
Interview candidates directly with technical questions relevant to your stack. We can facilitate or let you run it entirely. You decide.
Risk-Free Trial
Start with a 2-week trial. The engineer joins your team, attends standups, and delivers real work. If not a fit, we replace at no cost.
Scale as Needed
Add more data engineers or expand to a full data team Pod with analytics engineers, ML engineers, and platform specialists. We scale with your needs.
Engagement Options
Individual Engineers or Data Pods
Choose the model that fits your needs. Start with one engineer, scale to a full team.
Dedicated Data Engineer
A skilled data engineer who works as part of your team. You provide direction and reviews; they build and maintain your data infrastructure.
- Full-time dedication to your project
- Integrates with your processes and tools
- Participates in your standups and reviews
- Scale up or down as needed
Data Engineering Pod
A cross-functional team including data engineers, analytics engineers, and a tech lead. We handle delivery; you focus on what insights you need.
- Full accountability for data platform
- Built-in testing and code review
- SPARK™ framework for quality gates
- Tech lead for architecture decisions
Not sure which is right? Read our comparison guide
Ready to Hire Data Engineers?
Tell us about your data infrastructure and requirements. We'll present pre-vetted candidates within days, and you can start with a risk-free trial.
FAQs
Hire Data Engineers: Common Questions
Answers to frequently asked questions about hiring data engineers through Salt.
How quickly can I hire data engineers through Salt?
You can hire data engineers within 1-2 weeks. We present pre-vetted candidates within 2-3 days, you interview and select, and engineers can start with a 2-week trial. No lengthy recruitment cycles or months of searching.
What skills do your data engineers have?
Our data engineers are proficient in Python and SQL, data pipeline tools (Airflow, Prefect, Dagster), data warehouses (Snowflake, BigQuery, Redshift), transformation tools (dbt, Spark), and cloud platforms (AWS, GCP, Azure). Many also have experience with streaming systems like Kafka and Flink.
How do you vet data engineers before I hire them?
Our vetting includes live SQL and Python coding sessions, pipeline architecture design discussions, data modeling exercises, and assessment of debugging skills. We evaluate knowledge of data quality, performance optimization, and experience with production-scale data systems. Only about 3% pass.
Can I hire data engineers for my existing team?
Yes, absolutely. When you hire data engineers through Salt, they integrate seamlessly with your existing team, processes, and tools. They participate in your standups, code reviews, and planning sessions. We specifically match engineers who fit your tech stack and team culture.
Can I hire data engineers who also work with ML/AI?
Yes. Many of our data engineers have experience building feature stores, ML pipelines, and data infrastructure for data science teams. If you need dedicated ML expertise, we can also provide ML engineers or a Data/AI Pod.
What experience level are the data engineers I can hire?
Most data engineers you can hire through Salt have 4-8+ years of experience building production data systems. We categorize engineers as Mid-level (3-5 years), Senior (5-8 years), and Staff/Principal (8+ years) based on demonstrated skills, not just tenure.
Do your data engineers know dbt and modern transformation tools?
Yes. Our data engineers are proficient in dbt (including dbt Cloud and dbt Core), understand testing and documentation best practices, and can implement proper data modeling patterns. Many have experience migrating from legacy ETL tools to modern approaches.
What if I need to hire more data engineers later?
Scaling is built into our model. Start by hiring one data engineer, add more as needed, or transition to a full Data Pod with analytics engineers, ML engineers, and platform specialists. There's no penalty or friction for scaling up or down.
What time zones do your data engineers work in?
Our engineers are based in India but maintain 4-6 hours of overlap with US time zones. Many work flexible schedules to align with your team's core hours. We ensure there's enough real-time collaboration for effective teamwork.
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