Anailísí Sonraí TF/ IT Data Analyst

at  EirGrid Group

IF YOU BELIEVE YOU HAVE THE SKILLS AND EXPERIENCE RELEVANT FOR THIS POSITION, PLEASE UPLOAD YOUR CV AND A COVER LETTER. WE WANT TO HEAR FROM YOU.

Dáta deiridh d’iarratais/ Closing date for applications
08/07/2024

Knowledge, Skills and Experience

• A bachelor’s degree in data science, statistics, mathematics, computer science, or related field supported by typically 4 years’ experience working as a data analyst, BI analyst, or related profession.
• Proven experience with programming languages such as SQL, Python, and R for data manipulation and analysis.
• Proven experience with data analysis and visualization tools such as Power BI, Tableau, and Excel
• Expert knowledge of statistical analysis techniques and concepts for both descriptive and inferential analysis.
• Knowledge of data visualization best practices to effectively communicate insights.
• Strong analytical and problem-solving skills to interpret complex datasets and generate meaningful insights.
• Ability to work with large datasets through data cleaning, preprocessing, and transformation techniques, preferably using the Microsoft Azure Suite such as Data Factory, Fabric, or Data Bricks.
• Excellent communication skills to convey complex data findings to both technical and business executives.
• Attention to detail and ability to maintain data accuracy and integrity

EirGrid’s IT Strategy and Emerging Technology Team is ramping up its Data Program and is looking for a Data Analyst. We are seeking an IT Data Analyst to be responsible for interpreting and analysing complex datasets providing insights and support data-driven decision-making within EirGrid.
As the IT Data Analyst, you will works alongside data scientists, engineers, modelers, and business leaders to gather and transform data, conduct statistical analyses, and create impactful visualizations and reports that will contribute to identifying trends, patterns, and opportunities that drive business initiatives

Príomhfhreagrachtaí

• Tuiscint a bhaint as torthaí ag úsáid éagsúlacht anailíse staitistiúla.
• Próiseas bailithe agus glanta sonraí ó fhoinsí éagsúla inmheánacha agus seachtracha a chur i gcrích, chun iontaofacht agus caighdeán sonraí a chinntiú.
• Modhanna staitistiúla a úsáid chun patrúin, treochtaí, comhghaolta agus aimhrialtachtaí a aithint agus chun léargais fhiúntacha a bhaint astu.
• Deaiseanna, tuairiscí agus léirithe físiúla a fhorbairt agus a choinneáil chun torthaí sonraí a chur i láthair go héifeachtach.
• Comhoibriú le hinnealtóirí sonraí agus le gairmithe TF chun barr acmhainne a bhaint amach maidir le próisis bailiúcháin, stórála agus aisghabhála sonraí.
• Tacú le heolaithe sonraí agus cásanna casta úsáide sonraí á seachadadh.
• Monatóireacht a dhéanamh ar chaighdeán sonraí chun fhadhbanna sonraí a aithint agus réitigh glantacháin nó feabhsúcháin sonraí a mholadh.
• Bheith ar an eolas faoi na treochtaí agus dea-chleachtas is deireanaí san earnáil mar a bhaineann le hanailís, léiriú agus tuairisciú sonraí.

Key Responsibilities

• Interpret results using a variety of statistical analysis.
• Complete the gathering and cleaning process of data from various internal and external sources, ensuring data integrity and quality.
• Use statistical methods to identify patterns, trends, correlations, and anomalies, and extract meaningful insights.
• Develop and maintain dashboards, reports, and visualizations to communicate data findings effectively.
• Collaborate with data engineers and IT professionals to optimize data collection, storage, and retrieval processes.
• Support data scientists in the delivery of complex data use cases.
• Monitor data quality to identify data issues and propose data cleansing or enhancement solutions.
• Stay updated with industry trends and best practices in data analysis, visualization, and reporting.

Saineolas, Scileanna agus Taithí

• Céim Baitsiléara in eolaíocht sonraí, staitisticí, matamaitic, ríomh-eolaíocht nó ábhar gaolmhar, le taithí 3 bliana ag obair mar anailísí sonraí, anailísí intleachta gnó nó ról gaolmhar.
• Taithí chruthaithe le teangacha ríomhchlárúcháin ar nós SQL, Python, agus R d’ionramháil agus d’anailís sonraí.
• Taithí chruthaithe le uirlisí anailíse agus léirithe sonraí ar nós Power BI, Tableau agus Excel.
• Saineolas ar theicnící agus ar choincheapa anailíse staitistiúla d’anailís thuairisciúil agus infeireach araon.
• Eolas ar an dea-chleachtas léirithe sonraí chun léargais a chur i láthair go héifeachtach.
• Scileanna láidre anailísíochta agus réiteach fadhbanna chun tuiscint a bhaint as tacair chasta sonraí agus léargais fhiúntacha a ghiniúint.
• Cumas oibriú le tacair mhóra sonraí trí theicnící glantacháin, réamhphróiseála agus claochlaithe sonraí a úsáid, go hidéalach agus úsáid á baint as Microsoft Azure Suite, mar shampla Data Factory, Fabric, nó Data Bricks.
• Sárscileanna cumarsáide chun torthaí casta sonraí a chur in iúl d’fheidhmeannaigh theicniúla agus ghnó.
• Dírithe ar mhionsonraí agus in ann iontaofacht agus cruinneas sonraí a chinntiú.

Knowledge, Skills and Experience

• A bachelor’s degree in data science, statistics, mathematics, computer science, or related field supported by typically 4 years’ experience working as a data analyst, BI analyst, or related profession.
• Proven experience with programming languages such as SQL, Python, and R for data manipulation and analysis.
• Proven experience with data analysis and visualization tools such as Power BI, Tableau, and Excel
• Expert knowledge of statistical analysis techniques and concepts for both descriptive and inferential analysis.
• Knowledge of data visualization best practices to effectively communicate insights.
• Strong analytical and problem-solving skills to interpret complex datasets and generate meaningful insights.
• Ability to work with large datasets through data cleaning, preprocessing, and transformation techniques, preferably using the Microsoft Azure Suite such as Data Factory, Fabric, or Data Bricks.
• Excellent communication skills to convey complex data findings to both technical and business executives.
• Attention to detail and ability to maintain data accuracy and integrity.