Data Architect

HiQo Solutions

Rad od kuće

14.03.2025.

SQL Apache Oracle Python AWS SQL Server PostgreSQL Azure Cloud RedShift intermediate

Hello! It's nice to have you here! Let us introduce ourselves?

At HiQo we focus on developing entire IoT systems. We are US-based company, headquartered in Atlanta with delivery centers in Europe. We design devices, write software that brings them to life, and create applications that connect them to end users. We solve technological challenges from all over the world and we do it by creating something from scratch. And at the end of the day we get to have that special sense of tangible achievement that you don’t always get elsewhere.

Celebrating its 17th year anniversary, we’ve completed more than 1,500 projects worldwide.

We are looking for a skilled Data Architect with strong expertise in SQL, Python, and data warehousing. The ideal candidate will have experience with relational databases, cloud platforms (AWS/ Azure/ GCP) and building data pipelines. Knowledge of geospatial data systems and tools like QGIS, PostGIS and ArcGIS is a plus. If you're passionate about working with large datasets and optimizing data processes, we want to hear from you!

REQUIREMENTS:

1. Strong Knowledge of SQL

Proven experience in writing complex SQL queries and optimizing for performance.
Ability to work with relational databases (e.g., PostgreSQL, SQL Server, Oracle) to retrieve, transform, and manipulate large datasets.

2. Experience with Python

Strong experience using libraries such as NumPy, Pandas, and other data manipulation and analysis tools.

3. Hands-On Experience with Data Warehousing and Data Integration Tools

Practical experience in building and maintaining data pipelines and architectures.
Familiarity with at least of popular data warehousing solutions such as: Amazon Redshift, Google BigQuery, Snowflake, Microsoft Azure Synapse Analytics, Teradata, Apache Hive.
Experience in integrating data from various sources into a central data warehouse.

4. Familiarity with Cloud Platforms

Experience working with cloud platforms such as AWS, Azure, and Google Cloud Platform (GCP).
Understanding of cloud-based data storage, data lakes, and compute services, such as AWS S3, Azure Data Lake, GCP Cloud Storage, and EC2/Compute Engine.

DESIRABLE:

5. Familiarity with Geospatial Data Systems, Standards and Tools

Understanding of geospatial data formats and standards (e.g., GeoJSON, Shapefiles, WMS, WFS).
Experience working with geospatial data processing and analysis tools, such as: QGIS, PostGIS (Spatial extension for PostgreSQL), ArcGIS, GDAL (Geospatial Data Abstraction Library).
Familiarity with GIS (Geographic Information Systems) concepts and their application in data engineering.