Developer Jobs in Sumterville, FL

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Data Engineer

SUMTER ELECTRIC COOPERATIVE, INC Sumterville, FL

Sumterville, FL

Today

Full time Analytics Automation Developer Azure Data Engineer

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Job Description

Sumter Electric Cooperative, Inc is hiring a Data Engineer in Sumterville, FL (onsite) to design and operate governed data pipelines and lakehouse/warehouse data products.

Responsibilities

Design, build, test, deploy, and support modern data platform pipelines and lakehouse or warehouse data products.
Implement ingestion, staging, transformation, conformance, and publishing patterns across raw/bronze, stage, silver, gold, and certified consumption layers.
Build transformations using PySpark, Spark SQL, Python, and SQL that are distributed, restartable, idempotent, and operationally supportable.
Apply full-refresh, incremental, CDC, merge, and partition-aware load patterns where appropriate.
Design source registration, audit stamping, row hashing, metadata capture, and lineage-friendly table handling.
Create conformed dimensions, facts, bridge tables, reference tables, and curated marts for analytics and semantic model consumption.
Partner with business SMEs and analysts to define business keys, surrogate keys, grain, relationships, slowly changing dimension needs, and metric-ready structures.
Use metadata-driven configuration patterns for sources, tables, columns, jobs, schemas, quality rules, and load audits.
Support MDM-ready outputs and stewardship workflows for core entities such as customer, account, product, location, device, meter, vendor, or chart of accounts.
Maintain documentation for table contracts, lineage, refresh behavior, data quality rules, and operational dependencies.
Apply governance and security practices across data products, including access control, sensitivity awareness, ownership, cataloging, endorsement, certification, and audit evidence.
Support Microsoft Purview, OneLake catalog, or equivalent governance capabilities for lineage, data cataloging, domains, glossary terms, quality status, and data product discoverability.
Design solutions supporting domain-oriented ownership, data mesh principles, reusable platform patterns, and federated governance.
Ensure production reports and semantic models consume approved data products rather than unfinished engineering layers unless explicitly approved for validation.

Requirements

Minimum: Four (4) year bachelor’s degree from an accredited institution in computer science, information systems, data engineering, software engineering, mathematics, statistics, engineering, or a related technical field.
Minimum experience: Four (4) years of progressively responsible experience in data engineering, ETL/ELT development, analytics engineering, database development, BI engineering, software development, cloud data platform engineering, or related technical work.
Preferred: Certifications or formal training in Microsoft Fabric, Azure Data Engineer, Databricks, Spark, Snowflake, data governance, DevOps, data modeling, or cloud architecture.
Preferred: Experience designing and operating lakehouse or warehouse platforms, medallion data flows, Spark/PySpark workloads, Data Factory or pipeline orchestration, metadata-driven frameworks, dimensional models, master data, and governed semantic-ready marts.
Preferred: Experience with Microsoft Fabric, Azure Data Lake Storage, OneLake, Delta Lake, Synapse, Databricks, Snowflake, Power BI semantic models, Git-based DevOps, and enterprise operational data.
Ability to operate a variety of office equipment, including a personal computer, printers, copy machines, and telephone.
Ability to work irregular hours, including flexibility to change scheduling and report to work on short notice during emergency situations.
Irregular hours in evenings and on weekends are possible during peak business times and during storm season.
Normal work hours: eight (8) hours between 7:00 am and 5:00 pm, Monday through Friday.
Successful completion of pre-employment background check, physical, and drug screen.
Follows safety procedures diligently, identifies potential hazards, and takes appropriate action to maintain a safe working environment.
Provides exceptional service to members, actively listening to their needs and ensuring their satisfaction.
Acts with honesty and integrity in all tasks, maintaining transparency and ethical standards.
Demonstrates a strong work ethic by consistently meeting deadlines and achieving high performance in all tasks.
Contributes to an inclusive culture by respecting and valuing diverse perspectives and collaborating effectively with team members.
Takes responsibility for actions and decisions to meet commitments and deliver high-quality work.
Works collaboratively with team members, sharing information and supporting collective goals.

Key Technical Competencies

Engineering judgment to design reliable, scalable, secure, and maintainable data solutions aligned with organizational architecture and tradeoffs across performance, governance, and usability.
Using PySpark, Spark SQL, Python, and SQL to build scalable pipelines for ingestion, transformation, cleansing, enrichment, and validation, including performance optimization and avoiding distributed processing anti-patterns.
Operating modern lakehouse and warehouse platforms, including Fabric, ADLS, OneLake, Databricks, Snowflake, and Synapse, to architect and optimize scalable, secure, and governed data environments.
Leveraging Data Factory, Dataflows, notebooks, APIs, and orchestration tools to develop and maintain reliable pipelines that support operational resilience, monitoring, and production stability.
Dimensional modeling and analytical design using facts, dimensions, keys, slowly changing dimensions (SCDs), bridge tables, conformed dimensions, and aggregate structures for semantic models and BI solutions.
Governance frameworks for metadata, lineage, cataloging, auditability, and data quality, including validation controls such as reconciliation, integrity checks, and duplication detection aligned with security standards.
Applying MDM principles (entity resolution, survivorship, stewardship) and data-as-a-product thinking for governed, consumer-ready data products.
Using Git, CI/CD, code reviews, automated deployments, environment management, and versioning for controlled and repeatable delivery.
Knowledge of Power BI, Direct Lake, semantic models, gold-layer design, and performance-optimized analytics consumption.
Using AI tools (Fabric Copilot, code generation assistants) responsibly with validation, privacy compliance, and safe production usage.

Technologies

Microsoft Fabric
Azure data services
Azure Data Lake Storage
OneLake
Delta Lake
Databricks
Snowflake
Synapse
PySpark
Spark SQL
Python
SQL
ETL/ELT
CI/CD
Change data capture (CDC)
Data Factory
Dataflows
Notebooks
APIs
Git-based DevOps
Git
Power BI
Direct Lake
Microsoft Purview
Delta / open table formats
Dimensional modeling
Data mesh
Master data management (MDM)
DevOps
DataOps
Fabric Copilot

Additional Statements

Qualifications and competencies may be verified through a combination of education, experience, interview questions, and technical skills exercise(s).
Safety, service, honesty, integrity, work ethic, inclusion, responsibility, and collaboration expectations are part of the role.

Physical Demands and Work Environment

Regularly required to sit and talk or hear.
Occasionally required to walk; stand; use hands to finger, handle, or feel; reach with hands and arms; climb or balance; stoop, kneel, crouch, or crawl.
Must regularly lift and/or move up to 10 pounds.
Specific vision abilities required: close vision, distance vision, color vision, and ability to adjust focus.
General sedentary office environment; noise level usually moderate.

Workplace and Compliance

SECO Energy participates in E-Verify.
SECO Energy does not accept unsolicited resumes from any source other than directly from applicants.
This posting will be closed and no longer available to receive applications upon SECO Energy’s discretion.

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