Technical Consultant Data & Analytics, Business Intelligence, Data Engineer

Analytics and data engineering consultant with hands-on industry experience, computer-science background, state-of-the art tech know-how with strong project references and up-to-date certifications, and a career history that spans 14 years.

• Business Intelligence (BI)
• Consulting
• Data Analyst
• Data Engineering
• Python
• Team management

Analytics and data engineering consultant with hands-on industry experience, computer-science background, state-of-the art tech know-how with strong project references and up-to-date certifications, and a career history that spans 14 years across the Marketing Tech, E-Commerce, Enterprise Information Management domains, having managed data-driven professional services projects up to size of 1000 days and shipped more than 20 data products and pipelines into production.

I help organizations solve ambitious data processing and business intelligence problems, mapping business goals with data, automating data-driven workflows, visualizing to support decision-making, scaling in the cloud, tuned for the needs of teams and enterprise.

I am passionate about all things business intelligence automation, enabling workflows, building data solutions.

Core skills
• Building and optimizing analytics and business intelligence solutions
• Technical business analysis with dashboards, reporting, by using PowerBI, Python, Plotly Dash, Excel, Metabase, Orange, Google Data Studio, Streamlit
• Management & consulting of enterprise software projects and project teams, SaaS business algorithms and best practices
• Python programming language, analytics and data science with Anaconda stack, Scikit-learn, Keras, Numpy, Dask, datawarehousing with PostgreSQL & BigQuery, servers with Flask, big data analytics and processing with Apache Spark, containerization with Docker, secure and scalable GCP cloud backend solutions in production environments, ELT/ETL and workflow orchestration with Prefect & Spark.ML, CI/CD, DataOps and MLOps, building data products and data platforms, applied machine learning solutions

Complementary Skills (varying proficiency levels)
• Python: PyData (numpy,pandas,matplotlib,seaborn), REST APIs, RESTful microservices, asyncio, Flask, Cucumber with Python Behave, Selenium, Applied machine learning (scikit-learn, Keras)
• Software Engineering: Data structures & algorithms, OOP, TDD, design patterns, concurrency, dynamic programming, CI/CD
• Data Engineering: Big data processing: PySpark, Koalas, Dask and SaturnCloud; ELT/ETL pipelines and workflow orchestration: Prefect, Spark.ML, Luigi, Apache Airflow; Databases: PostgreSQL, MongoDB, ElasticSearch, MySQL, SQLite; Data integration: Kinesis Firehose; Cloud computing: GCP, AWS (S3,RDS,EC2,Kinesis Firehose,Gateway,Glue,Route53); Containerization: Docker, Kubernetes; Events: Kafka (Confluent); Data warehousing: BigQuery; Modeling: dbt data build tool, CI/CD: Github, Terraform, Ansible
• Data Science: Data retrieval, Data analysis, Data preparation, EDA, Feature engineering, Designing basic machine learning models or applying advanced ML models into production, Optimization algorithms, Recommender systems, Natural Language Processing
• SQL: Advanced queries, Stored procedures, UDF, Window functions
• Shell: Bash scripting, Makefiles
• E-Commerce / WCMS: Wordpress, wooCommerce, Magento
• Web development: VueJS, Full stack with Ruby on Rails & Hotwire, Javascript
• Digital marketing automation: HubSpot, SendGrid, SemRush, AdWords
• VisualBasic & VBA: Applications, Forms, DOM model manipulations
• C#: Console applications, using APIs
• Other: Build tools, package managers, Git version control, test automation