Database, Data Engineering, Cloud & AI consulting since 2007
ETL & BI
Reliable, well-monitored data pipelines that move and shape data for analytics, reporting, migrations and AI - using the tools that fit your platform.
Reports and AI models are only as good as the data feeding them. AVRIN designs, builds and operates enterprise-grade ETL and ELT pipelines that bring data together from line-of-business databases, SaaS applications, files and APIs - with validation, lineage and alerting built in.
We modernize legacy SSIS packages and scheduled scripts, introduce change data capture (CDC) for near real-time loads, and build data lakes and lakehouses that scale with your organization. Every pipeline is version-controlled, parameterized per environment, and documented.
Whether you are consolidating reporting on SQL Server, adopting Snowflake or Databricks, or feeding Power BI and machine learning workloads, we choose the simplest architecture that meets your latency, volume and budget requirements.
Experience across Microsoft, AWS and modern cloud data platforms.
Design, tuning and support of SQL Server Integration Services packages, SSIS catalog deployment, and migration of SSIS workloads to Azure Data Factory or Microsoft Fabric where it makes sense.
Cloud-scale orchestration with ADF pipelines and data flows, self-hosted integration runtimes for on-premises sources, and Fabric Data Factory for lakehouse-centric analytics.
AWS Database Migration Service for full-load and ongoing CDC replication between engines, and AWS Glue for serverless transformation into Amazon S3 data lakes and Redshift.
Lakehouse architectures on Delta Lake with the medallion (bronze, silver, gold) pattern, Spark-based transformation, Unity Catalog governance and machine learning integration.
Cloud data warehouse design, secure data sharing, Snowpipe ingestion, dbt or SQL-based ELT, and warehouse sizing to keep compute cost under control.
Talend data integration jobs, Python-based pipelines and open-source tooling where licensing or portability requirements call for it.
A data lake stores raw and curated data cheaply in open formats such as Parquet and Delta on Amazon S3, Azure Data Lake Storage or Google Cloud Storage. A lakehouse adds warehouse-style tables, transactions and governance on top.
We design zones, partitioning, security and retention so the lake stays usable - not a "data swamp".
Sources, volumes, latency requirements, data owners and quality issues.
Target architecture, data model, tool selection, security and cost estimate.
Pipelines as code, automated data validation and reconciliation against sources.
Monitoring, alerting, failure recovery and continuous performance tuning.
Need reporting on top of your pipelines? See our Power BI & reporting solutions or our AI & data services.
Contact AVRIN to review your current pipelines or plan a new data platform on SQL Server, Azure, AWS, Snowflake or Databricks.
