Mikhail Akimov
Data Team Lead
Tel-Aviv, Tel-Aviv District, Israel
Summary
👤
Senior🎓
Top SchoolMikhail Akimov is a Data Team Lead with 11 years of hands-on experience building analytics platforms, currently leading data efforts at Obligo from Tel-Aviv. He specializes in end-to-end analytics engineering—everything from ingesting disparate systems into warehouses (Vertica/Postgres) to transformation (dbt, SQL), orchestration (Airflow), testing and BI (Tableau)—and applies software engineering practices like CI, git and Docker to data work. Mikhail has repeatedly bootstrapped analytics systems for startups and large organisations, driving measurable efficiency gains (up to ~4 hours/day per employee) and retraining teams to sustain growth. He’s equally comfortable coding (Python) and contributing to open-source stream processing (python-streamz), where he improved partitioning and reliability features. A people-first manager, he has hired and mentored teams of data specialists whose careers progressed to top tech firms, reflecting his focus on talent development as the primary lever for impact. His background in humanities (MA in Arabic Language and Literature) gives him a rare edge in communication and domain understanding when translating complex business problems into data solutions.
11 years of coding experience
7 years of employment as a software developer
Lomonosov Moscow State University
Russian, English, Arabic
Github Skills (6)
hard-real-time10
realtime10
python10
async10
unit-testing8
tornado8
Programming languages (9)
Github contributions (5)
python-streamz/streamz
Mar 2020 - Nov 2020
Real-time stream processing for python
Role in this project:
Back-end Developer
Back-end DeveloperContributions:39 reviews, 33 commits, 11 PRs in 8 months
Contributions summary:Mikhail primarily focused on fixing bugs and implementing new features related to stream processing within the `streamz` library. Their work included addressing issues like streams overwriting buffer methods and passing metadata when using LRU caching. They also implemented the timeout and key routing functionality for partitioning streams and refactored sink operations. Overall, their contributions centered on improving the core functionality and reliability of the stream processing framework.
pythonstream-processingstreaming-dataasyncreal-time
discover-labs/dictum-backend-postgres
Jul 2022 - Nov 2023
Postgres backend for Dictum
Contributions:5 releases, 21 PRs, 41 pushes in 1 year 3 months
postgresqlbackendpostgres
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