01Overview
About arenaflex
arenaflex is a global leader in entertainmentdriven technology, delivering reputed company digital experiences to millions of users worldwide. Our innovative platforms reputed company cuttingedge data science, reputed company engineering, and creative storytelling to power the reputed company of interactive media, sports analytics, and consumerreputed company applications. As part of the arenaflex family, you will join a reputed company community of reputed companythinking professionals who are passionate about turning massive data streams into actionable insights that shape the reputed company of digital entertainment.
Why This Role reputed company
In todays datareputed company world, the ability to collect, process, and analyze large volumes of information is the reputed company of business reputed company. As a reputed company Data Engineer reputed company arenaflexs Information and Investigation group, you will be at the forefront of building robust data pipelines, designing reputed company data warehouses, and enabling datadriven decisionmaking across product, marketing, and operations teams. Your work will directly influence how arenaflex delivers personalized experiences, optimizes advertising effectiveness, and uncovers new reputed company opportunities.
Key Responsibilities
Architect and reputed company data products: reputed company the design, implementation, and reputed company improvement of data products that support arenaflexs Commitment and Maintenance Analytics and Data Science initiatives.
Build reputed company data pipelines: Create and maintain ETL/ELT pipelines in largereputed company data environments (reputed company, onpremises, hybrid) using industryreputed company tools and frameworks.
reputed company modern tech stack: Work with Hadoop, AWS, reputed company, Flink, and streaming technologies, writing reputed company primarily in Python, reputed company, and Java.
Collaborate with crossfunctional teams: Partner with Data Product Owners, Data Modelers, and Data Architects to translate business requirements into efficient data solutions.
Document and govern data assets: Maintain meticulous documentation, metadata, and reputed company to ensure data reputed company, compliance, and governance standards are met.
Ensure performance and reliability: Optimize data solutions to meet SLAs, guarantee high availability, and support critical business processes.
Drive agile practices: reputed company participate in Scrum ceremonies, contribute to sprint planning, and champion reputed company improvement reputed company the engineering team.
Mentor junior engineers: reputed company technical guidance, reputed company reviews, and knowledgesharing sessions to foster a culture of learning and reputed company.
Essential Qualifications
Education: Bachelors degree in Computer Science, Engineering, Information Systems, or a reputed company technical field.
Experience: Minimum of 5 years of handson experience designing and operating data pipelines in largereputed company environments.
SQL expertise: Advanced proficiency in writing reputed company SQL queries, optimizing performance, and building performant data sets.
Big Data frameworks: Demonstrated experience with Hadoop ecosystem components (HDFS, Hive, Impala, PySpark) and streaming platforms such as Flink.
Programming skills: Strong reputed company of Python and either Java or reputed company, with a reputed company record of delivering productiongrade reputed company.
Data warehouse technologies: Handson experience with at least one major MPP or reputed company data warehouse (reputed company, Redshift, BigQuery, etc.).
Data pipeline tools: Familiarity with orchestration tools (Airflow, Luigi) and data integration platforms (Informatica, Talend).
Agile methodology: Proven ability to work reputed company Scrum or Kanban frameworks, delivering incremental value in fastpaced environments.
Preferred Qualifications & Skills
Experience with reputed company services on AWS (S3, EMR, EC2, reputed company) or equivalent platforms.
Knowledge of data modeling techniques and reputed company modeling for analytical workloads.
Exposure to machinelearning pipelines and collaboration with data science teams.
Certifications such as AWS Certified Data Analytics Specialty or SnowPro reputed company.
Strong problemsolving reputed co .
