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Data Analytics Jobs in Forney, TX (NOW HIRING)

... Analytics background to support Corporate Sales Reporting and Analytics needs. The Data Analyst will partner with business and operations technology teams to define and execute data analytics ...

Analyze data to drive decision-making on new features of Wdesk * Suggest new product development priorities for Wdesk after gathering market data * Analyze use of Wdesk by current customers in the EU ...

Analyze data to drive decision-making on new features of Wdesk * Suggest new product development priorities for Wdesk after gathering market data * Analyze use of Wdesk by current customers in the EU ...

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Data Analytics information

See Forney, TX salary details

$22

$49

$85

How much do data analytics jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for data analytics in Forney, TX is $49.32, according to ZipRecruiter salary data. Most workers in this role earn between $39.62 and $55.87 per hour, depending on experience, location, and employer.

What is data analytics?

Data analytics is the process of examining raw data to uncover trends, patterns, and insights that can inform decision-making. Professionals in this field use statistical techniques, programming, and data visualization tools to interpret complex data sets. Data analytics is applied in various industries, including business, healthcare, finance, and technology, to optimize operations, improve customer experiences, and drive strategic initiatives. The field often requires knowledge of tools like Excel, SQL, Python, and specialized analytics platforms.

How does a data analytics professional typically collaborate with other departments within an organization?

Data Analytics professionals frequently work alongside teams such as marketing, finance, operations, and product development to identify trends, solve business problems, and inform strategic decisions. Collaboration often involves gathering data requirements, interpreting findings, and presenting actionable insights in a clear and accessible manner. Effective communication and the ability to translate technical data into business terms are essential for ensuring recommendations are implemented and drive measurable impact. Regular cross-functional meetings and project-based teamwork are common, offering opportunities to learn from other disciplines and broaden one's organizational influence.

What are the key skills and qualifications needed to thrive as a data analytics professional, and why are they important?

To thrive as a Data Analytics professional, you need strong quantitative analysis skills, proficiency in statistics, and a relevant degree such as in mathematics, computer science, or a related field. Experience with technical tools like SQL, Python or R, data visualization platforms (e.g., Tableau, Power BI), and sometimes certifications like Google Data Analytics or Microsoft Certified: Data Analyst Associate are highly valuable. Critical thinking, problem-solving, and effective communication are essential soft skills for interpreting data and presenting findings to stakeholders. These skills and qualities are crucial for transforming raw data into actionable insights that drive business decision-making.

What is the difference between Data Analytics vs Data Analyst?

AspectData AnalyticsData Analyst
Role FocusAnalyzing large datasets to identify trends and insightsInterpreting data, creating reports, and supporting decision-making
Skills & CertificationsStatistical skills, data visualization, tools like SQL, Python, RData visualization, Excel, SQL, basic statistical knowledge
Work EnvironmentOften in data teams, tech companies, or consulting firmsBusiness units, marketing, finance, or operations teams
Common UsageRefers to the field or disciplineRefers to the job role or position

While both roles involve working with data, Data Analytics typically refers to the broader field or discipline focused on analyzing data to extract insights. A Data Analyst is a specific job role within that field, responsible for interpreting data, creating reports, and supporting business decisions.

Is a data analyst still a good career?

Data analysts remain in high demand across industries due to the increasing reliance on data-driven decision making. Strong skills in tools like Excel, SQL, and visualization software, along with certifications, can enhance job prospects and career growth in this field.

What jobs can a data analyst do?

A data analyst can work in roles such as business analyst, data scientist, data engineer, or reporting specialist. They analyze data to help organizations make informed decisions, often using tools like Excel, SQL, and visualization software, and may require knowledge of statistical methods and programming languages like Python or R.

What kind of jobs can you get with data analytics?

Data analytics skills can lead to roles such as data analyst, business analyst, data scientist, and data engineer. These jobs involve analyzing data to support decision-making, often requiring proficiency in tools like Excel, SQL, and Python, and may require relevant certifications or a strong understanding of statistical methods.

What are the most commonly searched types of Data Analytics jobs in Forney, TX?

The most popular types of Data Analytics jobs in Forney, TX are:

What are popular job titles related to Data Analytics jobs in Forney, TX?

For Data Analytics jobs in Forney, TX, the most frequently searched job titles are:

What job categories do people searching Data Analytics jobs in Forney, TX look for?

The top searched job categories for Data Analytics jobs in Forney, TX are:

What cities near Forney, TX are hiring for Data Analytics jobs?

Cities near Forney, TX with the most Data Analytics job openings:

Infographic showing various Data Analytics job openings in Forney, TX as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $102,584 per year, or $49.3 per hour.

Data Analytics Lead Engineer

Citibank (Switzerland) AG

Irving, TX • On-site

$126 - $189/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted yesterday

New


Job description

Data Analytics Lead Engineer

Citi is looking for a Data Analytics Lead Engineer to design, build, and operate scalable data pipelines and cloud-based data architectures within our Lending business, spanning Mortgage and Personal Loans. This is a hands‑on data engineering role where you will develop and maintain production‑grade data systems — working across big data platforms, data lakes, and cloud infrastructure — that directly power lending analytics at scale. You will also bring an understanding of AI and ML integration as an additional capability applied within a strong data engineering foundation.


Responsibilities

  • Build, deploy, and manage end‑to‑end data pipelines that ingest, transform, and deliver large‑scale lending datasets across Mortgage and Personal Loans with high reliability and performance.

  • Design and implement scalable data architectures on cloud platforms, selecting the right tools and approaches across data lakes, data warehouses, and streaming environments.

  • Architect and implement data schemas — choosing from relational, dimensional, normalized, or partitioned models — to meet performance, scalability, and business requirements.

  • Write and optimize complex SQL queries against large‑scale datasets, applying sound decisions around distributed and parallel processing to improve pipeline efficiency.

  • Monitor, diagnose, and resolve operational and data quality issues across pipelines to ensure accuracy, completeness, and timely delivery of data.

  • Apply generative AI tools to accelerate core engineering tasks such as code generation, query optimization, and data summarization where appropriate.

  • Contribute to data engineering standards and collaborate with Business Analysts, Data Engineers, and Data Governance teams to translate business requirements into robust technical solutions.


Required Qualifications & Skills

  • 6+ years of hands‑on experience building and managing data pipelines, data warehouses, and data lake solutions using technologies such as Hadoop, Apache Spark, PySpark, Databricks, Delta Lake, Hive, Impala, and Iceberg.

  • Practical experience with cloud data platforms including Snowflake, Cloudera, used to build and automate ETL and data ingestion workflows.

  • Fluency in one or more scripting languages — Python, Scala, or Shell Scripting — applied actively to data engineering, pipeline development, and automation tasks.

  • Strong ability to design and query relational and non‑relational data stores, with a clear understanding of schema design trade‑offs and data modelling principles.

  • Hands‑on experience with workflow scheduling tools such as Autosys or Apache Airflow to manage and orchestrate data pipeline execution.

  • Confident use of DevOps practices including version control, build tools, unit testing, monitoring, and change management to support reliable and repeatable delivery.

  • Experience with data visualization platforms such as Tableau, Cognos to support data presentation and reporting needs.

  • A Bachelor's degree or equivalent university qualification; a Master's degree is preferred.


Beneficial Skills & Qualifications

  • Exposure to cloud‑based AI and ML services such as Amazon SageMaker, Azure Machine Learning, or Google AI Platform, used to integrate predictive models within data pipelines.

  • Familiarity with NoSQL database technologies such as HBase, MongoDB, Couchbase, Cassandra, or Neo4j.

  • Databricks certification or cloud platform certification in AWS, Azure, or GCP.

  • A proactive approach to troubleshooting — able to independently investigate root causes and resolve pipeline or data issues with thoroughness and pace.


What We Offer

We offer the technical scale and team environment to do meaningful engineering work, alongside the flexibility and investment to support your continued growth.



  • Hybrid working model with 3 days in the office and 2 days working remotely, providing flexibility alongside team collaboration.

  • Access to large‑scale, complex data environments and modern cloud infrastructure where your engineering decisions have direct business impact.

  • Continuous learning and technical development support, including backing for cloud and platform certifications relevant to your work.

  • A collaborative team of data engineers, analysts, and business partners where hands‑on technical contribution is valued and visible.

  • Competitive compensation and a comprehensive benefits package designed to support your financial and personal wellbeing.


Build the data foundations that power real lending decisions at global scale —


Other Information

Full time


Primary Location: Irving Texas United States


Salary Range: $125,760.00 - $188,640.00


Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire.


Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law. If you are a person with a disability and need a reasonable accommodation to use your search tools and/or apply for a career opportunity review Accessibility at Citi. View Citi's EEO Policy Statement and the Know Your Rights poster.


Anticipated Posting Close Date: Sept 09, 2026

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