{"id":55327,"date":"2020-01-18T00:00:00","date_gmt":"2020-01-17T21:00:00","guid":{"rendered":"https:\/\/prohoster.info\/blog\/blog_prohoster\/samye-vostrebovannye-navyki-v-professii-data-engineer"},"modified":"2020-02-18T14:03:26","modified_gmt":"2020-02-18T11:03:26","slug":"samye-vostrebovannye-navyki-v-professii-data-engineer","status":"publish","type":"post","link":"https:\/\/prohoster.info\/sk\/blog\/administrirovanie\/samye-vostrebovannye-navyki-v-professii-data-engineer","title":{"rendered":"Najvyh\u013ead\u00e1vanej\u0161ie zru\u010dnosti v profesii data engineer","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Pod\u013ea \u0161tatistike z roku 2019<\/a><\/noindex>, data engineer je v s\u00fa\u010dasnosti profesiou, na ktor\u00fa je dopyt rastie najr\u00fdchlej\u0161ie zo v\u0161etk\u00fdch. Data engineer zohr\u00e1va v organiz\u00e1ci\u00e1ch kritick\u00fa \u00falohu \u2013 vytv\u00e1ra a udr\u017eiava funk\u010dn\u00e9 pipeline a datab\u00e1zy, ktor\u00e9 sa pou\u017e\u00edvaj\u00fa na spracovanie, transform\u00e1ciu a uchov\u00e1vanie d\u00e1t. Ak\u00e9 zru\u010dnosti s\u00fa pre predstavite\u013eov tejto profesie najd\u00f4le\u017eitej\u0161ie? L\u00ed\u0161i sa zoznam od toho, \u010do sa po\u017eaduje od data scientistov? O v\u0161etkom tom sa dozviete z m\u00f4jho \u010dl\u00e1nku.<\/p>\n

Analyzoval som pracovn\u00e9 ponuky na poz\u00edciu data engineer v janu\u00e1ri 2020, aby som pochopil, ak\u00e9 technologick\u00e9 zru\u010dnosti s\u00fa naj\u017eiadanej\u0161ie. Potom som porovnal z\u00edskan\u00e9 v\u00fdsledky so \u0161tatistikou pracovn\u00fdch pon\u00fak na poz\u00edcie data scientist \u2013 pri\u010dom sa uk\u00e1zali niektor\u00e9 zauj\u00edmav\u00e9 rozdiely.<\/p>\n

Ob\u00eddeme sa bez dlh\u00fdch \u00favodov \u2013 tu je top desiatka technol\u00f3gi\u00ed, ktor\u00e9 sa naj\u010dastej\u0161ie spom\u00ednaj\u00fa v textoch pracovn\u00fdch pon\u00fak:<\/p>\n

\"Najvyh\u013ead\u00e1vanej\u0161ie<\/p>\n

Spom\u00ednania technol\u00f3gi\u00ed v pracovn\u00fdch ponuk\u00e1ch na poz\u00edciu data engineer v roku 2020<\/i><\/p>\n

Po\u010fme sa na to pozrie\u0165.
\n<\/a><\/noindex><\/p>\n

Povinnosti data engineer<\/h4>\n

\nV s\u00fa\u010dasnosti je pr\u00e1ca, ktor\u00fa vykon\u00e1vaj\u00fa data engineers, pre organiz\u00e1cie nesmierne d\u00f4le\u017eit\u00e1 \u2013 pr\u00e1ve t\u00edto \u013eudia s\u00fa zodpovedn\u00ed za uchov\u00e1vanie inform\u00e1ci\u00ed a d\u00e1vaj\u00fa ich do takej podoby, aby s nimi mohli pracova\u0165 aj ostatn\u00ed zamestnanci. Data engineers buduj\u00fa pipeline, aby zabezpe\u010dili z\u00edskavanie d\u00e1t pr\u00fadom alebo po d\u00e1vkach z mnoh\u00fdch zdrojov. N\u00e1sledne pipeline vykon\u00e1vaj\u00fa oper\u00e1cie extrakcie, transform\u00e1cie a nahr\u00e1vania (in\u00fdmi slovami, ETL procesy), \u010d\u00edm robia d\u00e1ta vhodnej\u0161\u00edmi na \u010fal\u0161ie vyu\u017eitie. Nakoniec s\u00fa d\u00e1ta predan\u00e9 analytikom a data scientists na h\u013abkov\u00fa anal\u00fdzu. Nakoniec kon\u010d\u00ed cesta d\u00e1t na informa\u010dn\u00fdch paneloch, v spr\u00e1vach a modeloch pre strojov\u00e9 u\u010denie.<\/p>\n

H\u013eadal som inform\u00e1cie, ktor\u00e9 by umo\u017enili dospie\u0165 k z\u00e1veru, ak\u00e9 technol\u00f3gie s\u00fa aktu\u00e1lne naj\u017eiadanej\u0161ie v pr\u00e1ci data engineer.<\/p>\n

Met\u00f3dy<\/h4>\n

\nZbieral som inform\u00e1cie zo troch pracovn\u00fdch webov \u2013 SimplyHired<\/a><\/noindex>, Indeed<\/a><\/noindex> a Monster<\/a><\/noindex> a sledoval, ak\u00e9 k\u013e\u00fa\u010dov\u00e9 slov\u00e1 sa objavuj\u00fa v kombin\u00e1cii s \u201edata engineer\u201c v textoch pracovn\u00fdch pon\u00fak ur\u010den\u00fdch pre obyvate\u013eov USA. Pri tejto \u00falohe som pou\u017eil dve kni\u017enice Python \u2013 Requests<\/a><\/noindex> a Beautiful Soup<\/a><\/noindex>. Do k\u013e\u00fa\u010dov\u00fdch slov som zahrnul nielen tie, ktor\u00e9 boli v predch\u00e1dzaj\u00facom zozname pre anal\u00fdzu pracovn\u00fdch pon\u00fak na poz\u00edciu data scientist, ale aj tie, ktor\u00e9 som manu\u00e1lne vybral pri \u010d\u00edtan\u00ed inzer\u00e1tov na pr\u00e1cu pre data engineers. LinkedIn nebol zahrnut\u00fd, preto\u017ee ma tam zablokovali po predch\u00e1dzaj\u00facej snahe zhroma\u017edi\u0165 \u00fadaje.<\/p>\n

Pre ka\u017ed\u00e9 k\u013e\u00fa\u010dov\u00e9 slovo som vypo\u010d\u00edtal percento v\u00fdskytu z celkov\u00e9ho po\u010dtu textov na jednotliv\u00fdch str\u00e1nkach a potom som vy\u010d\u00edslil priemern\u00fa hodnotu z troch zdrojov.<\/p>\n

V\u00fdsledky<\/h4>\n

\nNi\u017e\u0161ie je uveden\u00fdch tridsa\u0165 technick\u00fdch pojmov z oblasti data engineering s najvy\u0161\u0161\u00edmi hodnoteniami na v\u0161etk\u00fdch troch str\u00e1nkach pracovn\u00fdch pon\u00fak.<\/p>\n

\"Najvyh\u013ead\u00e1vanej\u0161ie<\/p>\n

A tu s\u00fa tie ist\u00e9 \u010d\u00edsla, ale prezentovan\u00e9 vo forme tabu\u013eky:<\/p>\n

\"Najvyh\u013ead\u00e1vanej\u0161ie<\/p>\n

Po\u010fme na to postupne.<\/p>\n

Preh\u013ead v\u00fdsledkov<\/b><\/p>\n

Aj SQL, aj Python sa nach\u00e1dzaj\u00fa vo vy\u0161e dvoch tretin\u00e1ch posudzovan\u00fdch pracovn\u00fdch pon\u00fak. Pr\u00e1ve tieto dve technol\u00f3gie m\u00e1 zmysel \u0161tudova\u0165 predov\u0161etk\u00fdm. Python<\/a><\/noindex> \u2013 ve\u013emi popul\u00e1rny programovac\u00ed jazyk, ktor\u00fd sa vyu\u017e\u00edva na pr\u00e1cu s \u00fadajmi, na vytv\u00e1ranie webov\u00fdch str\u00e1nok a na p\u00edsanie skriptov. SQL<\/a><\/noindex> sa roz\u0161iruje ako Structured Query Language (jazyk so \u0161trukt\u00farovan\u00fdmi dopytmi); predstavuje \u0161tandard, ktor\u00fd sa realizuje skupinou jazykov, a pou\u017e\u00edva sa na vy\u017eiadanie \u00fadajov z rela\u010dn\u00fdch datab\u00e1z. Objavil sa u\u017e d\u00e1vno a preuk\u00e1zal sa vysokou odolnos\u0165ou.<\/p>\n

O Sparku sa hovor\u00ed pribli\u017ene v polovici pracovn\u00fdch pon\u00fak. Apache Spark<\/a><\/noindex> \u2013 je to \u201eintegrovan\u00fd analytick\u00fd motor pre spracovanie ve\u013ek\u00fdch d\u00e1t so zabudovan\u00fdmi modulmi pre streamovanie, SQL, strojov\u00e9 u\u010denie a spracovanie grafov\u201c. Te\u0161\u00ed sa osobitnej popularite medzi t\u00fdmi, ktor\u00ed pracuj\u00fa s ve\u013ek\u00fdmi datab\u00e1zami.<\/p>\n

AWS sa objavuje pribli\u017ene v 45% textov pracovn\u00fdch pon\u00fak. Je to cloudov\u00e1 v\u00fdpo\u010dtov\u00e1 platforma od Amazonu; vlastn\u00ed najv\u00e4\u010d\u0161\u00ed podiel trhu medzi v\u0161etk\u00fdmi cloudov\u00fdmi platformami.
\nNasleduj\u00fa Java a Hadoop \u2013 nie\u010do vy\u0161e 40% na ka\u017ed\u00e9ho z nich. Java<\/a><\/noindex> \u2013 \u0161iroko pou\u017e\u00edvan\u00fd, v bojoch overen\u00fd jazyk, ktor\u00fd v ankete v\u00fdvoj\u00e1rov na Stack Overflow v roku 2019<\/a><\/noindex> obsadil desiate miesto medzi jazykmi, ktor\u00e9 vyvol\u00e1vaj\u00fa u program\u00e1torov hr\u00f4zu. Naopak, Python sa umiestnil na druhom mieste medzi jazykmi, ktor\u00e9 s\u00fa najviac milovan\u00e9. Jazykom Java riadi Oracle, a v\u0161etko, \u010do o \u0148om potrebujete vedie\u0165, pochop\u00edte z tejto sn\u00edmky obrazovky ofici\u00e1lnej str\u00e1nky z janu\u00e1ra 2020.<\/p>\n

\"Najvyh\u013ead\u00e1vanej\u0161ie
\n
\nA\u017e akoby som sa previezol \u010dasom<\/i>
\nApache Hadoop<\/a><\/noindex> pou\u017e\u00edva model programovania MapReduce s klastrami serverov na spracovanie ve\u013ek\u00fdch d\u00e1t. V s\u00fa\u010dasnosti sa od tohto modelu za\u010d\u00edna st\u00e1le \u010dastej\u0161ie up\u00fa\u0161\u0165a\u0165.<\/p>\n

\u010ealej vid\u00edme Hive, Scala, Kafka a NoSQL \u2013 ka\u017ed\u00e1 z t\u00fdchto technol\u00f3gi\u00ed sa spom\u00edna v \u0161tvrtine prezentovan\u00fdch pracovn\u00fdch miest. Apache Hive je program na ukladanie d\u00e1t, ktor\u00fd \u201eu\u013eah\u010duje \u010d\u00edtanie, p\u00edsanie a spr\u00e1vu ve\u013ek\u00fdch mno\u017e\u00edn d\u00e1t nach\u00e1dzaj\u00facich sa v distribuovan\u00fdch \u00falo\u017ei\u0161tiach pomocou SQL\u201c. Scala<\/a><\/noindex> \u2013 programovac\u00ed jazyk, ktor\u00fd sa akt\u00edvne vyu\u017e\u00edva pri pr\u00e1ci s ve\u013ek\u00fdmi d\u00e1tami. Konkr\u00e9tne, Spark bol vytvoren\u00fd v Scala. V u\u017e spom\u00ednanom rebr\u00ed\u010dku hroziv\u00fdch jazykov sa Scala umiest\u0148uje na jeden\u00e1stej prie\u010dke. Apache Kafka<\/a><\/noindex> \u2013 distribuovan\u00e1 platforma na spracovanie streamov\u00fdch spr\u00e1v. Je ve\u013emi popul\u00e1rna ako prostriedok na prenos d\u00e1t.<\/p>\n

NoSQL datab\u00e1zy<\/a><\/noindex> sa vyrovn\u00e1vaj\u00fa SQL. Odli\u0161uj\u00fa sa t\u00fdm, \u017ee nie s\u00fa rela\u010dn\u00e9, nie s\u00fa \u0161trukt\u00farovan\u00e9 a maj\u00fa horizont\u00e1lnu \u0161k\u00e1lovate\u013enos\u0165. NoSQL si z\u00edskalo ur\u010dit\u00fa popularitu, av\u0161ak hor\u00fa\u010dkovit\u00e9 nad\u0161enie t\u00fdmto pr\u00edstupom, a\u017e po proroctv\u00e1, \u017ee nahrad\u00ed SQL ako dominantn\u00fa paradigmu ukladania, sa zd\u00e1, \u017ee je u\u017e za nami.<\/p>\n

Porovnanie s term\u00ednmi v pracovn\u00fdch miestach data scientist<\/h4>\n

\nTu je tridsa\u0165 technologick\u00fdch term\u00ednov, naj\u010dastej\u0161ie sa vyskytuj\u00facich u zamestn\u00e1vate\u013eov v oblasti datovej vedy. Tento zoznam som z\u00edskal rovnak\u00fdm sp\u00f4sobom, ktor\u00fd som op\u00edsal vy\u0161\u0161ie pre datov\u00e9 in\u017einierstvo.<\/p>\n

\"Najvyh\u013ead\u00e1vanej\u0161ie<\/p>\n

Zmienky o technol\u00f3giach v pracovn\u00fdch miestach pre poz\u00edciu data scientist v roku 2020<\/i><\/p>\n

Ak hovor\u00edme o celkovom po\u010dte, v porovnan\u00ed so sk\u00f4r presk\u00faman\u00fdm s\u00faborom, bylo viac pracovn\u00fdch miest o 28% (12 013 oproti 9 396). Pozrime sa, ktor\u00e9 technol\u00f3gie sa vyskytuj\u00fa v pracovn\u00fdch miestach pre data scientistov menej \u010dasto ako pre data in\u017einierov.<\/p>\n

Ob\u013e\u00fabenej\u0161ie v datovom in\u017einierstve<\/b><\/p>\n

Na grafe ni\u017e\u0161ie s\u00fa zobrazen\u00e9 k\u013e\u00fa\u010dov\u00e9 slov\u00e1 s priemern\u00fdm rozdielom v hodnot\u00e1ch vy\u0161\u0161\u00edm ako 10% alebo ni\u017e\u0161\u00edm ako -10%.<\/p>\n

\"Najvyh\u013ead\u00e1vanej\u0161ie<\/p>\n

Najv\u00e4\u010d\u0161ie rozdiely v frekvencii k\u013e\u00fa\u010dov\u00fdch slov medzi data engineerom a data scientistom<\/i><\/p>\n

Najv\u00fdraznej\u0161\u00ed n\u00e1rast vykazuje AWS: v datovom in\u017einierstve sa objavuje o 25% \u010dastej\u0161ie ako v datovej vede (pribli\u017ene 45% a 20% z celkov\u00e9ho po\u010dtu pracovn\u00fdch miest). Rozdiel je zna\u010dn\u00fd!<\/p>\n

Tu s\u00fa rovnak\u00e9 \u00fadaje v trochu inej podobe \u2013 na grafe s\u00fa v\u00fdsledky pre rovnak\u00e9 k\u013e\u00fa\u010dov\u00e9 slovo v pracovn\u00fdch miestach na poz\u00edciu data engineer a data scientist umiestnen\u00e9 ved\u013ea seba.<\/p>\n

\"Najvyh\u013ead\u00e1vanej\u0161ie<\/p>\n

Najv\u00e4\u010d\u0161ie rozdiely v frekvencii k\u013e\u00fa\u010dov\u00fdch slov medzi data engineerom a data scientistom<\/i><\/p>\n

Nasleduj\u00faci najv\u00e4\u010d\u0161\u00ed skok som zaznamenal pri Spark \u2013 data engineer \u010dasto pracuje s ve\u013ek\u00fdmi d\u00e1tami. Kafka<\/a><\/noindex> tie\u017e vzr\u00e1stol o 20 %, teda takmer \u0161tyrikr\u00e1t v porovnan\u00ed s v\u00fdsledkami pre data scientist. Prenos \u00fadajov je jednou z k\u013e\u00fa\u010dov\u00fdch povinnost\u00ed data engineer. Nakoniec sa po\u010det zmienok uk\u00e1zal o 15 % vy\u0161\u0161\u00ed v oblasti data engineeringu pri Java, NoSQL, Redshift, SQL a Hadoop.<\/p>\n

Menej popul\u00e1rne v data engineeringu<\/b><\/p>\n

Teraz sa pozrime, ktor\u00e9 technol\u00f3gie s\u00fa menej popul\u00e1rne v inzer\u00e1toch pre data engineer.
\nNajv\u00fdraznej\u0161\u00ed pokles v porovnan\u00ed s oblas\u0165ou data science nastal pri R<\/a><\/noindex>: tam bol spomenut\u00fd pribli\u017ene v 56 % inzer\u00e1tov, tu \u2013 iba v 17 %. P\u00f4sobiv\u00e9. R je programovac\u00ed jazyk, ktor\u00fd je \u00faspe\u0161n\u00fd medzi vedcami a \u0161tatistikmi a obsadil \u00f4sme miesto v rebr\u00ed\u010dku najhor\u0161\u00edch jazykov.<\/p>\n

SAS<\/a><\/noindex> takisto sa v inzer\u00e1toch na poz\u00edciu data engineer objavuje cite\u013ene menej \u2013 rozdiel je 14 %. SAS je patentovan\u00fd jazyk ur\u010den\u00fd na pr\u00e1cu so \u0161tatistikami a d\u00e1tami. Zauj\u00edmav\u00fd moment: s\u00fad pod\u013ea v\u00fdsledkov mojho v\u00fdskumu inzer\u00e1tov pre data scientists<\/a><\/noindex>, v poslednej dobe dramaticky stratil poz\u00edcie \u2013 viac ne\u017e ak\u00e1ko\u013evek in\u00e1 technol\u00f3gia.<\/p>\n

Vy\u017eadovan\u00e9 ako v data engineeringu, tak aj v data science<\/b><\/p>\n

Je potrebn\u00e9 poznamena\u0165, \u017ee osem z desiatich prv\u00fdch poz\u00edci\u00ed v oboch s\u00faboroch s\u00fa rovnak\u00e9. SQL, Python, Spark, AWS, Java, Hadoop, Hive a Scala sa dostali do desiatky ako pre oblas\u0165 data engineeringu, tak aj pre data science. Na grafe ni\u017e\u0161ie m\u00f4\u017eete vidie\u0165 p\u00e4tn\u00e1s\u0165 najpopul\u00e1rnej\u0161\u00edch technol\u00f3gi\u00ed u zamestn\u00e1vate\u013eov data engineers, a ved\u013ea nich \u2013 ich hodnota v inzer\u00e1toch pre data scientists.<\/p>\n

\"Najvyh\u013ead\u00e1vanej\u0161ie<\/p>\n

Odpor\u00fa\u010dania<\/h4>\n

\nAk sa chcete venova\u0165 data engineeringu, odpor\u00fa\u010dam v\u00e1m osvoji\u0165 si nasleduj\u00face technol\u00f3gie \u2013 uv\u00e1dzam ich v porad\u00ed pribli\u017enej prioritiz\u00e1cie.<\/p>\n

Osvojte si SQL. Odpor\u00fa\u010dam v\u00e1m najm\u00e4 PostgreSQL, preto\u017ee m\u00e1 otvoren\u00fd k\u00f3d, ve\u013ek\u00fa popularitu v komunite a nach\u00e1dza sa vo f\u00e1ze rastu. Ako pou\u017e\u00edva\u0165 jazyk sa m\u00f4\u017eete dozvedie\u0165 z knihy My Memorable SQL \u2013 jej pilotn\u00e1 verzia je k dispoz\u00edcii tu<\/a><\/noindex>.<\/p>\n

Osvojte si Python, aj ke\u010f nie na najhardcornej\u0161ej \u00farovni. Kniha My Memorable Python je ur\u010den\u00e1 pr\u00e1ve pre za\u010diato\u010dn\u00edkov. M\u00f4\u017eete ju zak\u00fapi\u0165 na Amazon<\/a><\/noindex>, elektronick\u00fa k\u00f3piu alebo fyzick\u00fa, pod\u013ea v\u00e1\u0161ho v\u00fdberu, alebo si ju m\u00f4\u017eete stiahnu\u0165 vo form\u00e1te pdf alebo epub na tejto str\u00e1nke<\/a><\/noindex>.<\/p>\n

Akon\u00e1hle sa obozn\u00e1mite s Python, prejdite na pandas \u2013 kni\u017enicu Python, ktor\u00e1 sa pou\u017e\u00edva pri \u010disten\u00ed a spracovan\u00ed \u00fadajov. Ak sa chcete zamestna\u0165 vo firme, kde sa vy\u017eaduje schopnos\u0165 programova\u0165 v Pythone (a tak\u00fdch je v\u00e4\u010d\u0161ina), m\u00f4\u017eete si by\u0165 ist\u00ed, \u017ee znalos\u0165 pandas bude predpokladan\u00e1 automaticky. Pr\u00e1ve dokon\u010dujem \u00favodn\u00fd sprievodca pre pr\u00e1cu s pandas \u2013 m\u00f4\u017eete sa prihl\u00e1si\u0165<\/a><\/noindex>, aby ste nezme\u0161kali moment jeho vydania.<\/p>\n

Osvojte si AWS. Ak chcete by\u0165 data engineer, bez cloudovej platformy sa nezaob\u00eddete, a AWS je najpopul\u00e1rnej\u0161ia z nich. Mne ve\u013emi pomohli kurzy Linux Academy<\/a><\/noindex>, ke\u010f som \u0161tudoval data engineering na Google Cloud<\/a><\/noindex>, mysl\u00edm, \u017ee aj o AWS tam n\u00e1jdete dobr\u00e9 materi\u00e1ly.<\/p>\n

Ak u\u017e ste zvl\u00e1dli cel\u00fd tento zoznam a chcete e\u0161te viac posilni\u0165 svoj postoj v o\u010diach zamestn\u00e1vate\u013eov ako data engineer, navrhujem prida\u0165 Apache Spark pre pr\u00e1cu s ve\u013ek\u00fdmi \u00fadajmi. Hoci moje vyh\u013ead\u00e1vanie pracovn\u00fdch pon\u00fak v oblasti data science nazna\u010dilo pokles z\u00e1ujmu, u data engineerov sa st\u00e1le objavuje v ka\u017edej druhej ponuke.<\/p>\n

Na z\u00e1ver<\/h4>\n

\nD\u00fafam, \u017ee tento preh\u013ead naj\u017eiadanej\u0161\u00edch technol\u00f3gi\u00ed pre data engineer bol pre v\u00e1s u\u017eito\u010dn\u00fd. Ak v\u00e1s zauj\u00edma, ak\u00e1 je situ\u00e1cia s pracovn\u00fdmi ponukami pre analytikov, pre\u010d\u00edtajte si m\u00f4j \u010fal\u0161\u00ed \u010dl\u00e1nok<\/a><\/noindex>. Prajem \u00faspe\u0161n\u00e9 in\u017einierstvo!
\n
Zdroj: habr.com<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

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