Assistant Store Manager HI KA MAKANA ALI'I at AT&T

Job Description:

About the Company:

At AT&T, we are connecting the world through the latest tech, top-of-the-line communications and the best in entertainment. Our groundbreaking digital solutions provide intuitive and integrated experiences for millions of customers across online, retail and care channels. Join our mission to deliver compelling communication and entertainment experiences to customers around the world as we continue to evolve as a technology-powered, human-centered organization. As part of our team, you will transform the way we deliver a seamless customer experience with digital at the center of all you do. In our world, digital is much larger than just an eCommerce channel, we are transforming all channels to digitally perform as one team to create a better customer experience. As we move into 2023, the digital transformation will revolutionize the digital space and you can build a career that will propel your future.

About the Team:

As a Lead Software Engineer, you will join our dynamic Digital Engineering and Customer Experience (DECX) organizations Automation & AI team. This team is dedicated to enhancing customer experiences while ensuring that connected consumer journeys remain at the center of everything we do.

Job Summary:

We're seeking a Lead Software Engineer with a focus on Data Engineering, building, and maintaining data pipelines, building near real time operational data sources and real-time streaming data solutions to enhance our customer facing products while enabling predictive Machine Learning and AI solutions. The ideal candidate will play a pivotal role in the setup and implementation of appropriate data architecture and development of near real-time operational data stores and streaming data for consumption by customer facing applications and development and deployment of ML models for prediction of customer behavior. Key responsibilities include real-time ODS architecture and build, designing scalable data pipelines with low latency, enable the implemention and optimization of ML models, and enhance current data collection procedures. The candidate will also be tasked with exploring new data acquisition opportunities and responsible for the set-up of appropriate datasets that will allow for analyzing and visualizing data leveraging Power BI or any one of relevant tools (Kibana/Grafana/Tableau). Looking for a candidate who is staying updated with industry trends and ensuring adherence to AT&Ts strict security and data privacy guidelines.

Roles and Responsibilities:

Design and build low latency, near real-time operational data stores to support multiple consuming applications.

Design and develop real-time data streaming and data caching for applications to consume.

Design, build, and maintain robust, scalable data pipelines.

Collaborate closely with data scientists and application developers to understand data and latency requirements and provide appropriate solutions to implement, optimize, and maintain applications performance and predictive machine learning models.

Manage and optimize data systems that will help to generate actionable predictive insights.

Design and build large and complex data sets from various sources, while strategically considering the uses of data and its interaction with data design.

Explore new opportunities for data acquisition and enhance data collection to augment the existing datasets.

Perform data studies and data discovery around new data sources or new uses for existing data sources.

Visualize and report data findings creatively in various visual formats that accurately provide insights to the organization.

Primary skills:

Over 10 years of experience in Data Engineering and architecture enabling real time streaming and development of real time operational data stores, with working knowledge in data science, analytics, and data warehousing.

Extensive experience in data integration and Event/Stream Driven Architecture

Expert knowledge and experience applying Event/Stream Driven Architecture patterns from design to implementation.

Implementation expertise in data streaming technologies such as Kafka, Amazon MSK, Amazon Kinesis and/or Cloudera Kafka

Working experience in designing and building near real-time operational data stores.

Experience with entire data lifecycle including information architecture, data architecture, data management, data integration, data ingestion, data security, data privacy, data governance, and data analytics.

Knowledge of Edge processing solutions with low-latency, low-bandwidth and low power utilization scenarios as examples of edge requirements.

Prior experience in building datasets to support predictive machine learning algorithms, which include but are not limited to Supervised and Unsupervised learning techniques, Tree-based Modeling, Neural Networks, along with proficiency in various analytics tools and frameworks.

Technical prowess in data modeling, data mining, ETL, architectures, and data warehousing.

Familiarity in using Databricks for big data processing, building machine learning models, and data analytics.

Strong understanding of Apache Spark, as Databricks is a unified analytics platform for Apache Spark.

Experience in implementing ETL (Extract, Transform, Load) processes using Databricks.

Knowledge of programming languages like Python, Scala, and SQL

Familiarity with Machine Learning algorithms and the ability to support implementing them using Databricks MLflow is a plus.

Proficiency with one or more these technologies and platforms - Snowflake, Hadoop, SQL, Postgres SQL, Vertica, Redis, Splunk and Mongo DB.

Expertise in SQL (MySQL, Postgres SQL) and NoSQL databases (Mongo DB, Cassandra, Azure Cosmos DB), as well as Distributed Databases or Big Data solutions (Apache Spark, Cloudera, Vertica).

Knowledge of cloud services (AWS, Google Cloud, or Azure) and understanding of distributed data processing frameworks.

Proven ability to manage and delegate work across delivery teams to meet priorities.

Skill in client engagements, deciphering client business needs, and providing data solution recommendations.

Financial analysis skills to assess business impacts of statistical solutions.

Excellent communication skills, with experience in designing, developing, and delivering presentations.

Education Qualification: Preferred Bachelor of Science in Computer Science, Statistics, Math or Scientific Computing; or certification with equivalent experience value add.

Location: Plano/Dallas, Texas

Our Lead Software Engineering earns between $143,800.00-$215,800.00., Not to mention all the other amazing rewards that working at AT&T offers. Individual starting salary within this range may depend on geography, experience, expertise, and education/training.

AT&T is leading the way to the future for customers, businesses, and the industry. We are developing new technologies to make it easier for our customers to stay connected to their world. Together, weve built a premier integrated communications and entertainment company and an amazing place to work and grow. Team up with industry innovators every time you walk into work, creating the world you always imagined.

Ready to #transformdigital with us? Apply now!

Weekly Hours:

40

Time Type:

Regular

Location:

Plano, Texas

Salary Range:

$143,800.00 - $215,800.00

It is the policy of AT&T to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, AT&T will provide reasonable accommodations for qualified individuals with disabilities.