FinTechStack: Yandex.Cloud, Kafka, Airflow, S3, Greenplum, Python, Spark

Stack: python, sql, yql, greenplum, yt (hadoop)Achievements:1. Developed a custom framework for data quality controlin our storage, refning its architecture, gathering businessrequirements, and developing a solution capable of conductingdata checks on a table within 5 minutes. After a year of use bymultiple teams, a production-grade solution was built based onmy code.2. Took responsibility for the subject area, serving as both a systemanalyst and data engineer alongside monetization sector analysts.Successfully implemented a signifcant incremental data pipeline(20+ objects, generating $3,270,000 per month)3. Accelerated an important data transfer from Greenplum toHadoop by parallelizing the data loading process. (reduced from3 hours to 1 hour)4. I accelerated an important data pipeline about AB-tests (resultingin a 4-hour profit).5. Led, mentored, and served as the lead developer on a projectencompassing over 60 objects across various layers from start tofnish (resulting in a 4-hour profit).6. Worked with three different technology stacks. Greenplum, YT(Hadoop), YQL (Hive). Data modelling with HNHM, Data Vault,Anchor Modelling, Kimball.

Stack: SQL, Hadoop, Apache DrillIn my first role as a Data Engineer, I handled diverse subject areas,including government institutions, schools, and COVID-19 infectionrates, compiling reports for the mayor's offce. Despite facing tightdeadlines and working independently, I gained valuable skills inbuilding data pipelines and processing data effciently."However, due to various challenges and a misalignment ofexpectations, including the absence of a stable team and a lack ofmutual understanding with my supervisor, I experienced burnout andmade the decision to transition to a new role. This experience taughtme the importance of effective teamwork and communication, whichI have since prioritized in my career progression.

Stack: greenplum, powerbi, qliksense, oracle bi, ms sassAchievements:1. Implemented 25+ new reports that helped the business makenumerous decisions.2. Introduced various technological solutions, including a complexQlikSense map calculation that enabled analysis frommacro-regions down to individual households. This involved usingheat maps and various coloring and sizing techniques to visualizemetrics.3. I quickly mastered the technology stack and actively sought toinnovate the company's approach to BI, as many business clientswere unfamiliar with dashboards and relied solely on Excel.4. I challenged a lot of issues with vast amount of data (more than 2billion rows rows in SASS)