Ведущий эксперт в “Data Governance” (Направления по управлению данными)

Описание

A sy lk h an
Is m ailo v

i s m ailo v1 314@ gm ail. c o m

A sy lk h an
Is m ailo v
|
T e le gra m

g it h ub.c o m /a iz e ld




E XPER IE N CE

T a rg etA I
lt d
. Ta rg e ta i. k z

Vid eo
pro ce ssin g
AI
In fr a str u ctu re .
Data
en gin ee r

M ay
2024
– Pre se n t

• U se d
sta ck :
Clic k h o use ,
Ic e b erg
+ Parq uet
+ Min io ,
Sp ark .

• B uilt
a 3-n o de
Min IO
S3
clu ste r
wit h
Apach e
Ic e b erg
fo r
man agin g
ra w
an d
cu ra te d
data se ts ,
im ple m en te d
Sp ark

pip elin es
to
ge n era te
BI- r e ad y
data
marts
in
Ic e b erg ,
querie d
th ro ugh
Trin o
fo r
an aly tic s
an d
re p o rtin g

• M onit o re d
in te rn al
sy ste m s
acro ss
300+
se rv e rs
in
20+
dis tr ib ute d
en vir o nm en ts
, ca p tu rin g
ca m era
uptim e,
activ it y
le ve ls ,

bit ra te s,
FP S,
an d
oth er
crit ic a l
opera tio nal
metr ic s.

A ctiv e ly
man age d
pro ductio n
is su es— fr e q uen t
cra sh es
were
co m m on
due
to
in co nsis te n t
in te rn et
SLA s
in
Kaza kh sta n ,

makin g
re al- t im e
monit o rin g
an d
re co ve ry
cru cia l.

• In te re stin g
pro je ct:
Fo r
a B2B
an aly tic s
so lu tio n,
built
a pip elin e
to
id en tif y
uniq ue
daily
cu sto m ers ,
se gm en tin g
by
ho ur,

ge n der,
age
gro up,
activ it y
zo nes,
beh avio ur
,a n d
peak
en ga ge m en t
tim es
usin g
DBSC A N
clu ste rin g,
wit h

Air flo w -P ySp ark
orc h estra tio n.

• O th er
exp erie n ce :
Ngin x,
Ro ck y
lin ux,
Ansib le .
Deliv e re d
so lu tio ns
prim arily
fo r
B2G
clie n ts ,
dep lo yin g
data
in fr a str u ctu re

sy ste m s
on-p re m is e s
in
is o la te d
netw ork s.


I n te llig en ce
Sys te m s
lt d
.
Agro Te ch
sta rtu p,

o n-t ra ck .a i
. Pyth o n
Deve lo per

D ec
2022–
Apr
2024

• U se d
Backe n d
sta ck
: Dja n go ,
DRF,
Fa sta p i,
Po stg re s,
Sq la lc h em y,
Asy n cio .

• O th er
exp erie n ce :
Ngin x,
Docke r,
Te le gra m
bo t,
Gre en plu m ,
Ansib le ,
Gra fa n a
+ Vic to ria
metr ic s.

• D eve lo ped ,
an d
main ta in ed
backe n d
main
crm
pla tfo rm
usin g
Dja n go
an d
DRF.
Desig n ed
an d
orc h estra te d
ET L
pip elin es

in
Apach e
Air flo w

in te gra tin g
Io T
se n so r
data ,
weath er
APIs ,
an d
sa te ll it e
im age ry
in to
Gre en plu m
fo r
an aly tic s
an d

re p o rtin g

• M ig ra te d
a 2+
TB
sin gle -n o de
Po stg re SQ L
in sta n ce
to
a dis tr ib ute d
Gre en p lu m
6 MPP
clu ste r
(4
no des:
1 maste r,
1
sta n dby,
2 se gm en t
ho sts
wit h
3 se gm en ts
each ;
to ta l
~5
TB ).
Desig n ed
sp ecif ic a lly
fo r
sto rin g
an d
pro ce ssin g
an d
la rg e

JO IN S
betw een
Io T
se n so r
data ,
sa te llit e
im age ry ,
an d
in te gra tio n
wit h
exte rn al
sy ste m s
(1
с Bit r ix ).
Dra stic a lly
im pro ve d

query
perfo rm an ce
via
dis tr ib utio n
ke y
alig n m en t,
re p lic a te d
dim en sio ns,
an d
tim e-b ase d
partit io nin g.

• D eve lo ped
APIs
fo r
dash bo ard s,
su ch
as
cro p
str u ctu re ,
en han ce d
pla n nin g
accu ra cy
an d
im pro ve d
asse t
utiliz a tio n,
als o

Key
data
in clu ded
th o se
fo r
weig h in gs
an d
yie ld s,
en ab lin g
pre cis e
tra ck in g
of
cro p
perfo rm an ce ,
fo r
fie ld w ork
an d

eq uip m en t
fu el
co nsu m ptio n
an d
monit o rin g

• D eve lo ped
a Te le gra m
ale rtin g
bo t
to
pro vid e
re al- t im e
no tif ic a tio ns
ab o ut
eq uip m en t
in cid en ts
an d
crit ic a l
opera tio nal

in cid en ts
in
th e
fie ld ,
desig n ed
sp ecif ic a lly
fo r
fie ld
work e rs
wit h
lo w -c o st
pho nes
th at
ca n no t
han dle
nativ e
mobile

ap ps,
als o
en su rin g
in te rn et
acce ssib ilit y
in
lo w -c o nnectiv it y
zo nes.
It
sig n if ic a n tly
im pro ve d
re sp o nse
tim es
an d

opera tio nal
eff ic ie n cy.

• L e d
dep lo ym en t
of
backe n d
an d
DW H
se rv ic e s
to
se rv e rs ,
usin g
Ansib le
an d
Bash ,
use d
Lin ux
( Ubuntu
) fo r
pro du ctio n

en vir o nm en ts .
Su ppo rte d
th e
mig ra tio n
of
data
fr o m
le ga cy
pla tfo rm
to
a new
pla tfo rm .
Monit o re d
all
sy ste m

perfo rm an ce
th ro ugh
Gra fa n a
.



P et-P ro je cts

( in
Git h ub)




• R eal- t im e
Data
pro ce ssin g
an d
str e am in g
to ol
wit h
data
sto ra ge ,
utili z in g
Ran d o m use r
ap i
as
data
so urc e .
(A pach e
Air flo w ,

Kafk a ,
Sp ark ,

Cassa n dra )


• R estfu l
Backe n d
web -p ro je ct
wit h
re al- t im e
fa ce
re co gn it io n
fe atu re s
th ro ugh
web
ca m era ,
Mongo D B
Atla s
as
Clo ud

Data b ase .
(N ode.js ,
Vue3 js ,
Fa ce
re co gn it io n
Model
, Mongo D B)


• R eal- t im e
sto ck
pric e
pre d ic tio ns
usin g
ML
model
an d
vis u aliz in g
wit h
web -a p p
usin g
Po ly g o n.io
as
API
sto ck
pric e

so urc e (F a sta p i,
Vue3 js ,
Kafk a ,
LS T M
model)

E DU CATIO N



Asta n a
IT
Univ e rs it y
Asta n a,
Kaza kh sta n
So ft w are
En g in eer,
Gro u p:
SE -2 20 3
Se p .
202 2
– Ju ly
2025

GPA :
3.4 1 /4 .0





S OFT
SK IL LS


G allu p
te st.
Str e n gth :
Ach ie ve r,
le arn er,
re sp o nsib ili t y ,
co m petit iv e .

P ers o nalit y
: EN TJ-T
(C om man der).

P ro ble m
- so lv in g:
Resu lt s
an d
busin ess
orie n te d .

T im e
man age m en t:
Cre atin g
re p o rts
on
my
days
usin g
AnyTy p e,
Ato m ic
hab it s ,

P o m odo ro
meth o d.