Upstaff’s Guide to Hire Data and Analytics Team in 2025

Data Science, Analytics and Engineering Team
Need a vetted Data expert for big data, capable of designing pipelines, scalable storage and data analytics? Upstaff connects you with top SQL, ETL, Big Data, Apache Spark, Snowflake, and Kafka talent in 72 hours. Beat the 2025 hiring data engineering team chaos with our proven process.
Data Science, Analytics and Engineering Team

Meet Upstaff’s Vetted Data Engineer Developers

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AWS big data services 5yr.
Microsoft Azure 3yr.
Python
ETL
AWS ML (Amazon Machine learning services)
Keras
Machine Learning
OpenCV
TensorFlow
Theano
C#
C++
Scala
Apache Spark
Apache Spark 2
Big Data Fundamentals via PySpark
Deep Learning in Python
Linear Classifiers in Python
Pandas
PySpark
.NET
.NET Core
.NET Framework
Apache Airflow
Apache Hive
Apache Oozie 4
Data Analysis
Superset
Apache Hadoop
AWS Database
dbt
HDP
Microsoft SQL Server
pgSQL
PostgreSQL
Snowflake
SQL
AWS
GCP
AWS Quicksight
AWS Storage
GCP AI
GCP Big Data services
Kafka
Kubernetes
OpenZeppelin
Qt Framework
YARN 3
SPLL
...

- Data Engineer with a Ph.D. degree in Measurement methods, Master of industrial automation - 16+ years experience with data-driven projects - Strong background in statistics, machine learning, AI, and predictive modeling of big data sets. - AWS Certified Data Analytics. AWS Certified Cloud Practitioner. Microsoft Azure services. - Experience in ETL operations and data curation - PostgreSQL, SQL, Microsoft SQL, MySQL, Snowflake - Big Data Fundamentals via PySpark, Google Cloud, AWS. - Python, Scala, C#, C++ - Skills and knowledge to design and build analytics reports, from data preparation to visualization in BI systems.

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Seniority Expert (10+ years)
Location Ukraine
Data Analysis 10yr.
Python
Prompt Engineering
C#
Elixir
JavaScript
R
NumPy
TensorFlow
ASP.NET Core Framework
ASP.NET MVC Pattern
Entity Framework
caret
dplyr
rEDM
tidyr
dash.js
Flask
Matplotlib
NLTK
Pandas
Plotly
SciPy
Shiny
Basic Statistical Models
Chaos Theory
Cluster Analysis
Decision Tree
Factor Analysis
Jupyter Notebook
Linear and Nonlinear Optimization
Logistic regression
Multi-Models Forecasting Systems
Nearest Neighbors
Nonlinear Dynamics Modelling
Own Development Forecasting Algorithms
Principal Component Analysis
Random Forest
Ridge Regression
Microsoft SQL Server
PostgreSQL
AWS
GCP
Anaconda
Atom
R Studio
Visual Studio
Git
RESTful API
Windows
...

- 10+ years in Forecasting, Analytics & Math Modelling - 8 years in Business Analytics and Economic Processes Modelling - 5 years in Data Science - 5 years in Financial Forecasting Systems - Master of Statistics and Probability Theory (diploma with honours), PhD (ABD) - BSc in Finance - Strong knowledge of Math & Statistics - Strong knowledge of R, Python, VBA - Strong knowledge of PostgreSQL and MS SQL Server - 3 years in Web Development: Knowledge of C#, .Net and JavaScript for web development - Self-motivated, conscientious, accountable, addicted to data processing, analysis & forecasting - Engineering, Understanding AI and LLMs

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Seniority Senior (5-10 years)
Location Ukraine
Scala
NLP
Akka
Apache Spark
Akka Actors
Akka Streams
Cluster
Scala SBT
Scalatest
Apache Airflow
Apache Hadoop
AWS ElasticSearch
PostgreSQL
Slick database query
AWS
GCP
Haddop
Microsoft Azure API
ArgoCD
CI/CD
GitLab CI
Helm
Travis CI
GitLab
HTTP
Kerberos
Kafka
RabbitMQ
Keycloak
Swagger
Kubernetes
Terraform
Observer
Responsive Design
Unreal Engine
...

Software Engineer with proficiency in data engineering, specializing in backend development and data processing. Accrued expertise in building and maintaining scalable data systems using technologies such as Scala, Akka, SBT, ScalaTest, Elasticsearch, RabbitMQ, Kubernetes, and cloud platforms like AWS and Google Cloud. Holds a solid foundation in computer science with a Master's degree in Software Engineering, ongoing Ph.D. studies, and advanced certifications. Demonstrates strong proficiency in English, underpinned by international experience. Adept at incorporating CI/CD practices, contributing to all stages of the software development lifecycle. Track record of enhancing querying capabilities through native language text processing and executing complex CI/CD pipelines. Distinguished by technical agility, consistently delivering improvements in processing flows and back-end systems.

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Seniority Senior (5-10 years)
Location Ukraine
Azure 5yr.
Python 4yr.
SQL 5yr.
Cloudera 2yr.
Apache Spark
JSON
PySpark
XML
Apache Airflow
AWS Athena
Databricks
Data modeling Kimbal
Microsoft Azure Synapse Analytics
Power BI
Tableau
AWS ElasticSearch
AWS Redshift
dbt
HDFS
Microsoft Azure SQL Server
NoSQL
Oracle Database
Snowflake
Spark SQL
SSAS
SSIS
SSRS
AWS
GCP
AWS EMR
AWS Glue
AWS Glue Studio
AWS S3
Azure HDInsight
Azure Key Vault
API
Grafana
Inmon
REST
Kafka
databases
...

- 12+ years experience working in the IT industry; - 12+ years experience in Data Engineering with Oracle Databases, Data Warehouse, Big Data, and Batch/Real time streaming systems; - Good skills working with Microsoft Azure, AWS, and GCP; - Deep abilities working with Big Data/Cloudera/Hadoop, Ecosystem/Data Warehouse, ETL, CI/CD; - Good experience working with Power BI, and Tableau; - 4+ years experience working with Python; - Strong skills with SQL, NoSQL, Spark SQL; - Good abilities working with Snowflake and DBT; - Strong abilities with Apache Kafka, Apache Spark/PySpark, and Apache Airflow; - Upper-Intermediate English.

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Seniority Senior (5-10 years)
Location Norway
Python 9yr.
SQL 6yr.
Power BI 5yr.
Databricks
Selenium
Tableau 5yr.
NoSQL 5yr.
REST 5yr.
GCP 4yr.
Data Testing 3yr.
AWS 3yr.
R 2yr.
Shiny 2yr.
Spotfire 1yr.
JavaScript
Machine Learning
PyTorch
Spacy
TensorFlow
Apache Spark
Beautiful Soup
Dask
Django Channels
Pandas
PySpark
Python Pickle
Scrapy
Apache Airflow
Data Mining
Data Modelling
Data Scraping
ETL
Reltio
Reltio Data Loader
Reltio Integration Hub (RIH)
Sisense
Aurora
AWS DynamoDB
AWS ElasticSearch
Microsoft SQL Server
MySQL
PostgreSQL
RDBMS
SQLAlchemy
AWS Bedrock
AWS CloudWatch
AWS Fargate
AWS Lambda
AWS S3
AWS SQS
API
GraphQL
RESTful API
CI-CD Pipeline
Unit Testing
Git
Linux
MDM
Mendix
RPA
RStudio
BIGData
Cronjob
Parallelization
Reltio APIs
Reltio match rules
Reltio survivorship rules
Reltio workflows
Vaex
...

- 8 years experience with various data disciplines: Data Engineer, Data Quality Engineer, Data Analyst, Data Management, ETL Engineer - Automated Web scraping (Beautiful Soup and Scrapy, CAPTCHAs and User agent management) - Data QA, SQL, Pipelines, ETL - Data Analytics/Engineering with Cloud Service Providers (AWS, GCP) - Extensive experience with Spark and Hadoop, Databricks - 6 years of experience working with MySQL, SQL, and PostgreSQL; - 5 years of experience with Amazon Web Services (AWS), Google Cloud Platform (GCP) including Data Analytics/Engineering services, Kubernetes (K8s) - 5 years of experience with PowerBI - 4 years of experience with Tableau and other visualization tools like Spotfire and Sisense; - 3+ years of experience with AI/ML projects, background with TensorFlow, Scikit-learn and PyTorch; - Extensive hands-on expertise with Reltio MDM, including configuration, workflows, match rules, survivorship rules, troubleshooting, and integration using APIs and connectors (Databricks, Reltio Integration Hub), Data Modeling, Data Integration, Data Analyses, Data Validation, and Data Cleansing) - Upper-intermediate to advanced English, - Henry is comfortable and has proven track record working with North American timezones (4hour+ overlap)

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Seniority Senior (5-10 years)
Location Nigeria
Python 6yr.
SQL 6yr.
Apache Airflow
Apache Spark
AWS
Azure Data Factory 2yr.
Databricks 2yr.
AWS SageMaker
AWS SageMaker (Amazon SageMaker)
TensorFlow
FastAPI
Pandas
PySpark
Airbyte
Apache Hive
Azure Data Lake Storage
Data Analysis Expressions (DAX)
ETL
Jupyter Notebook
Looker Studio
Power BI
Sigma Compute
Superset
Tableau
Apache Hadoop
Aurora
AWS Redshift
Clickhouse
dbt
DWH
Firebase Realtime Database
HDFS
Microsoft Azure SQL Server
Microsoft SQL Server
MySQL
Oracle Database
PL/SQL
PostgreSQL
Snowflake
GCP
Amazon RDS
AWS Aurora
AWS CloudTrail
AWS CloudWatch
AWS EMR
AWS Lambda
AWS Quicksight
AWS R53
AWS S3
Azure Databricks
Azure MSSQL
Google BigQuery
Google Cloud Storage
CI/CD
Docker
Kubernetes
Github Actions
Grafana
Prometheus
Kafka
Apache Kafka
AWS Cloud9
database
DAX Studio
Google Cloud SQL
OpenMetadata
Relational
Spark EMR
Trino
Unix\Linux
...

* Experienced Data Engineer and BI Developer with 6+ years of expertise in Database Design and Business Intelligence Development. * Proficient in cloud technologies such as Amazon Web Services (AWS), Google Cloud Platform, and Microsoft Azure. * Skilled in building high-performance data integration and workflow solutions, including ETL operations for data warehousing and supporting OLAP, OLTP, and Data warehouse systems. Experience in optimizing DWH performance and automating data pipelines; * Modern data engineer skills such as data modeling, data warehousing, data lake, data governance, and data quality. * Experience with big data technologies such as Hadoop, Spark, and Kafka, and experience with data streaming and real-time data processing. * Proficiency in SQL and NoSQL databases, Snowflake, and ClickHouse * Data visualization tools such as Tableau or Power BI. * Programming languages such as Python, Java, or Scala, and understanding of machine learning concepts, with experience building and deploying machine learning models. * Experience with CI/CD, data governance, and security best practices.

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Seniority Senior (5-10 years)
Location Tashkent, Uzbekistan
Python
Julia
Machine Learning
NumPy
PyTorch
Scikit-learn
Matplotlib
Pandas
Data Analysis
ETL
ML
Power BI
dbt
SQL
Azure
Azure Data Studio
Google Data Studio
API
Authentication
Security
CI/CD
Git
MatLab
REST
Data Scientist
Function Apps
Microsoft Azure
MLOps
ML Studio
PHY
Version Control
...

- Applied data scientist and MLOps engineer with 5+ years in PHY security and ML for wireless systems. - End-to-end ML delivery: data wrangling, feature engineering, model development (scikit-learn, PyTorch), evaluation, and CI-friendly deployment. - Built ML-driven performance measurement and scheduling/optimization services; exposed via REST APIs; productionized on Microsoft Azure (ML Studio, Function Apps). - Strong data engineering foundation: SQL modeling and queries (Azure Data Studio), data pipelines, and reproducible experimentation. - Methods expertise: supervised/unsupervised learning, reinforcement learning, adversarial/robust modeling, optimization techniques. - Practical MLOps: containerized services, API design, monitoring-oriented deployment patterns, version control (Git). - Domain background: physical-layer authentication, anti-jamming/anti-spoofing, and federated/edge learning research. - Track record of translating complex problem statements into scalable, measurable data products with clear product impact.

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Seniority Senior (5-10 years)
Location Netherlands
Python 8yr.
AWS
R 1yr.
AI
AWS SageMaker
AWS SageMaker (Amazon SageMaker)
BERT
GPT
Keras
Kubeflow
Mlflow
NumPy
OpenCV
PyTorch
Spacy
TensorFlow
C++
Apache Spark
Beautiful Soup
NLTK
Pandas
PySpark
Apache Airflow
AWS Athena
ML
Power BI
AWS ElasticSearch
AWS Redshift
Clickhouse
SQL
AWS EC2
AWS ECR
AWS EMR
AWS S3
AWS Timestream (Amazon Time Series Database)
Apache HTTP Server
API
OpenAPI
CI/CD
Eclipse
Grafana
Kafka
MQQT
Kubernetes
ArcGIS
Data Processing
Guroby
ONNX
Open Street Map
Query
Rasa NLU
...

- Senior Python/ML Engineer with 10+ years in IT and 8+ years of professional Python experience; - Experienced in API and backend development with Python, data processing using Pandas/NumPy, and automation scripting; - Deep SQL expertise, including query optimization and database operations; - Experience with Apache Airflow, Apache Kafka, and Apache Spark/PySpark for data processing and workflow orchestration; - Strong Skills in ML/NLP frameworks such as TensorFlow, PyTorch, BERT, NLTK, and spaCy; - Extensive AWS experience (S3, Athena, EMR, Redshift, SageMaker) and Kubernetes for scalable deployments; - Built and deployed end-to-end ML pipelines and integrated AI solutions into business workflows; - Leadership as an ML engineering team lead.

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Seniority Senior (5-10 years)
Location Poland

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Table of Contents

How and where is Data Engineering used?

  • Real-time data processing: Collecting and analyzing data instantly
  • Data warehousing: Storing and managing large volumes of data efficiently
  • Data migration: Transferring data between systems seamlessly
  • Data modeling: Designing data structures for optimal performance
  • ETL processes: Extracting, transforming, and loading data accurately
  • Big data analytics: Handling and analyzing massive datasets effectively
  • Data quality management: Ensuring data accuracy and consistency
  • Streamlining workflows: Automating data pipelines for efficiency
  • Machine learning integration: Preparing data for AI and ML algorithms
  • Scalability optimization: Scaling data infrastructure for growth

TOP Data Engineering Related Technologies

  • Apache Hadoop (Distributed storage and processing framework by Apache, released in 2006, Doug Cutting, 2006)
  • Apache Spark Apache’s in-memory computation tool, released in 2014
  • Python: Author Guido van Rossum, 1991
  • Scala: Scala is a multi-paradigm programming language, created by Martin Odersky, designed to combine object-oriented and functional programming features, and first released in 2004.
  • Airflow: Open-source platform by Apache, released in 2014
  • Kafka: A distributed event streaming platform by Apache, released in 2011
  • Flink: Distributed streaming dataflow engine by Apache, released in 2016
  • Beam: Unified programming model by Apache, released in 2016
Table of Contents

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Our journey starts with a 30-min discovery call to explore your project challenges, technical needs and team diversity.
Manager
Maria Lapko
Global Partnership Manager

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FAQs on Data Engineering Development

What is a Data Engineering Developer? Arrow

A Data Engineering Developer is a specialist in the Data Engineering framework/language, focusing on developing applications or systems that require expertise in this particular technology.

Why should I hire a Data Engineering Developer through Upstaff.com? Arrow

Hiring through Upstaff.com gives you access to a curated pool of pre-screened Data Engineering Developers, ensuring you find the right talent quickly and efficiently.

How do I know if a Data Engineering Developer is right for my project? Arrow

If your project involves developing applications or systems that rely heavily on Data Engineering, then hiring a Data Engineering Developer would be essential.

How does the hiring process work on Upstaff.com? Arrow

Post Your Job: Provide details about your project.
Review Candidates: Access profiles of qualified Data Engineering Developers.
Interview: Evaluate candidates through interviews.
Hire: Choose the best fit for your project.

What is the cost of hiring a Data Engineering Developer? Arrow

The cost depends on factors like experience and project scope, but Upstaff.com offers competitive rates and flexible pricing options.

Can I hire Data Engineering Developers on a part-time or project-based basis? Arrow

Yes, Upstaff.com allows you to hire Data Engineering Developers on both a part-time and project-based basis, depending on your needs.

What are the qualifications of Data Engineering Developers on Upstaff.com? Arrow

All developers undergo a strict vetting process to ensure they meet our high standards of expertise and professionalism.

How do I manage a Data Engineering Developer once hired? Arrow

Upstaff.com offers tools and resources to help you manage your developer effectively, including communication platforms and project tracking tools.

What support does Upstaff.com offer during the hiring process? Arrow

Upstaff.com provides ongoing support, including help with onboarding, and expert advice to ensure you make the right hire.

Can I replace a Data Engineering Developer if they are not meeting expectations? Arrow

Yes, Upstaff.com allows you to replace a developer if they are not meeting your expectations, ensuring you get the right fit for your project.