Hire the Best Northern Data Systems EDIFICE Specialists

I build data pipelines and cloud warehouses that replace manual reporting, connect fragmented systems, and give teams data they can actually trust. My core work is GCP data engineering: BigQuery, Airflow, dbt, Python, SQL, ETL/ELT, API integrations, and data warehouse optimization. I also work across AWS, PostgreSQL, Redshift, and mixed legacy environments. I can help with: • AWS/GCP data infrastructure and cross-system integrations • ETL/ELT pipeline development and optimization • BigQuery data warehouse design, migration, and cost optimization • Airflow orchestration and production pipeline reliability • dbt transformations and analytics-ready data models • REST/API integrations and automated data ingestion • Legacy database and ETL migration to GCP • Python and SQL data engineering The technical work is only part of the job. I care about whether the pipeline is reliable, observable, maintainable, and actually useful to the people consuming the data. If you're dealing with unreliable pipelines, manual data work, slow reporting, expensive warehouse queries, or disconnected systems, send me the current setup and what you're trying to achieve. I'll give you a direct assessment of the best way to solve it.

DATA ENGINEER | BI EXPERT Are you looking to transform fragmented enterprise data into reliable, production-grade analytics pipelines? I am a Data Engineer with 8+ years of experience specializing in end-to-end ETL/ELT engineering, modern data lakehouse architectures, and scalable Business Intelligence (BI) systems. I bridge the gap between complex data architecture and business strategy, ensuring your stakeholders always have access to high-integrity, analytics-ready datasets. CORE EXPERTISE: 🔹 Data Pipelines & Orchestration: Designing and deploying resilient, scalable ETL/ELT pipelines using Python and dbt across Azure and AWS. Experience with migrating legacy workflows (SSIS, Pentaho Kettle) into modern cloud infrastructures. 🔹 Lakehouse Architecture: Implementing high-performance Delta Lake Medallion structures (Bronze, Silver, Gold) and dimensional modeling (Star and Snowflake schemas) optimized for query speed and minimal redundancy. 🔹 App & API Integrations: Ingesting and unifying data from disparate sources including Salesforce (deep data architecture expertise), HubSpot, Zendesk, Xero, Google Analytics, and AWS S3. 🔹 Modern Engineering Practices: Enforcing robust CI/CD version control via Git, automated data validation, and AI-assisted workflows to maximize pipeline uptime and accelerate script prototyping. 🔹 BI & Dashboarding: Creating actionable, executive-ready reports and dashboards to drive data-backed business decisions. 🔹 BI Platforms: Power BI, Tableau, Metabase, and Yellowfin BI. Whether you need a legacy system migration, a brand-new cloud data warehouse architecture, or optimized BI reporting, I deliver secure, secure-by-design, and production-grade solutions.

Hi, I'm Movses, a Data Engineer with 10+ years of experience. I'm a certified AWS Data Engineer with extensive experience in the AWS data stack. You name it, I've done it. More than data engineering, I love database development. With Oracle, Postgres, SQL Server, Snowflake, I feel home. SQL is my native language, and I code in Python, Scala, PL/SQL, and Bash. I specialize in creating ETL/ELT jobs, data pipelines, and orchestration jobs. I'm here to help you overcome challenges and set optimal data goals and designs. I stay involved after the project wraps up, not for the money, but because I only take on projects that genuinely interest me. I believe in delivering results that matter to both of us.

I build and maintain the data infrastructure that businesses run their reporting and analytics on from ingestion and transformation to reliable, automated pipelines. I work across the full data engineering stack: extracting data from APIs, files, and databases, modeling and transforming it, and automating the workflows that keep it flowing without manual intervention. Clients use this so their data is clean, structured, and always up to date without babysitting a pipeline by hand. What I do best: - ETL/ELT pipeline design and automation (Python, n8n) - SQL database design, querying, and optimization (PostgreSQL, MySQL, SQL Server) - API and multi-source data integration - Data modeling and cleaning at scale - Workflow automation for recurring data jobs Tools: Python (Pandas, NumPy, Scikit-learn), SQL, ETL pipelines, n8n, Power BI/Tableau (for downstream reporting when needed) I focus on building pipelines that are reliable, maintainable, and don't break when the data changes shape.