About Us

Data Engineering

Over 10 years of experience in data engineering, with a strong emphasis on developing robust data pipelines using Python for automation and scripting, combined with advanced SQL expertise for querying, optimization, and relational database management.
Specialized in designing and implementing modern data architectures, focused on scalability, performance, and high availability. This includes in-depth knowledge of cloud storage solutions, distributed computing frameworks, and both streaming and batch data processing pipelines for resilient and efficient data systems.
More than 25 years of experience as a database architect and engineer/developer.
Extensive experience in administering and working with highly transactional relational databases, including Microsoft SQL Server and PostgreSQL.
Proficient in building ETL/ELT data pipelines utilizing Debezium and Kafka, targeting analytical databases such as Greenplum, Vertica, and Hadoop.
Advanced programming skills in Python.

Skilled in containerization and orchestration tools, including Docker and Kubernetes.
Experience working with Helm for Kubernetes package management.
Hands-on experience with leading cloud platforms, including AWS and GCP.
Proficient with infrastructure-as-code and configuration management tools, such as Ansible and Terraform.
Strong understanding of CI/CD pipelines and GitOps workflows.
Expertise in database administration for systems like PostgreSQL and Microsoft SQL Server.
Familiarity with network protocols (TCP, IP, UDP) and routing protocols.
Proficient in Python programming and Bash scripting.
In-depth knowledge of Linux environments.

Design and development of complex stored procedures, functions, triggers, and views
Advanced indexing strategies, including clustered, non-clustered, full-text, and JSON/GIN indexes
Expertise in query tuning and optimization using execution plans, query store, hints, and statistics
Implementation of partitioning strategies for managing large datasets
Optimization using columnstore indexes and in-memory OLTP

Implementation of Always On Availability Groups (SQL Server)
Experience with log shipping, database mirroring, and replication
Failover clustering for both Windows and PostgreSQL environments
Point-in-Time Recovery (PITR) and Write-Ahead Logging (WAL) archiving in PostgreSQL
Development of comprehensive backup strategies, including full, differential, incremental, PITR, and snapshots

Role-based access control (RBAC) and fine-grained permission management
Implementation of Transparent Data Encryption (TDE) and row-level security
Usage of Dynamic Data Masking and Always Encrypted features (SQL Server)
Experience in data auditing and compliance with regulations such as GDPR and HIPAA
Secure database configuration and vulnerability assessment practices

Development using SQL Server Integration Services (SSIS)
Use of PostgreSQL Foreign Data Wrappers (FDW)
Expertise in data migration and transformation, including ETL pipelines, Change Data Capture (CDC), and bulk insert operations
Proficiency in handling data formats including JSON, XML, and CSV

Automation through scripting using Python and Bash
Infrastructure as code (IaC) for database environments using Terraform
Deployment of containerized PostgreSQL databases with Docker
Cloud-based database management across platforms such as Azure SQL, Amazon RDS, and Google Cloud SQL
Monitoring and observability using Prometheus, Grafana, and SQL Server Profiler