Key Responsibilities and Required Skills for Teradata Developer

🎯 Role Definition

As a Teradata Developer, you will be responsible for designing, building, optimising and maintaining high‑performance data warehouse solutions on the Teradata platform. Your work spans from requirements gathering and data modelling to ETL/ELT pipelines, utility scripting, performance tuning, production support and collaboration across cross‑functional teams. You’ll play a key role in ensuring data integrity, query performance, scalability and operational reliability of large‑scale Teradata environments often supporting mission‑critical analytics and reporting.

📈 Career Progression

Typical Career Path

Entry Point From:

SQL Developer or Database Developer working with relational warehouses
ETL Developer or Data Integration Engineer
Data Warehouse Analyst with hands‑on experience in Teradata or similar platforms

Advancement To:

Senior Teradata Developer / Lead Data Warehouse Engineer
Teradata Architect or Data Warehouse Architect
Director of Data Engineering, Head of Analytics Platform or Chief Data Architect

Lateral Moves:

Big Data Engineer with cloud‑warehouse emphasis (Snowflake, Redshift, etc.)
Cloud Data Platform Engineer specialising in Teradata‑to‑cloud migrations
Data Performance Specialist / Database Optimisation Lead

Core Responsibilities

Primary Functions

Analyse complex business requirements and source systems, design and implement Teradata data models (star/snowflake schemas), staging structures and enterprise data warehouse tables.
Develop, test and deploy ETL/ELT processes using Teradata utilities such as FastLoad, MultiLoad, TPump, FastExport, BTEQ and TPT to load high volumes of data efficiently.
Optimise SQL queries, stored procedures, macros and views in Teradata, using explain plans, statistics, partitioning, indexing and other performance‑tuning techniques.
Collaborate with data architects, business analysts and data consumers to interpret reporting needs, convert into technical design and implement ETL solutions and datasets accordingly.
Monitor, troubleshoot and tune Teradata systems for data skew, workload management (TASM/Workload‑class), spool space, disk I/O and query concurrency to maintain high availability and performance.
Write and maintain Unix/Linux shell scripts (or other automation) to support Teradata workflows, job scheduling (Control‑M, Autosys) and batch loads.
Participate in full software development lifecycle (SDLC) or agile processes: requirements gathering, design, development, unit testing, system/integration testing, UAT and production deployment.
Ensure data quality and integrity by performing source‑target reconciliation, data profiling, error handling, audit logging and correcting data issues.
Create and maintain documentation: technical specifications, data flow diagrams, mapping documents, run‑books, versioning of code and change‑logs for Teradata projects.
Manage migrations from legacy systems or other platforms into Teradata, including mapping, extraction, transformation, data load and cut‑over planning.
Maintain and enforce standards, best practices and governance for Teradata development: naming conventions, coding standards, resource usage and performance baselines.
Participate in or lead production support activities: incident triage, root‑cause analysis, patching, system upgrades and ensure minimal business impact of ETL/data‑warehouse failures.
Work with infrastructure and DBA teams on capacity planning, space management, archival strategies, table partitioning, and spool/disk usage for Teradata environment.
Develop reusable components, frameworks, templates or utilities (e.g., loading wrappers, parameterised scripts) to accelerate Teradata development and reduce maintenance overhead.
Support downstream BI/reporting teams by providing optimised data sets, aggregated views, ensuring timely data delivery and supporting analytics workflows.
Stay current with emerging Teradata features (such as Teradata Vantage), cloud/VM deployments, scalable architectures and recommend enhancements to architecture.
Perform data modelling and semantic layer coordination: work with ERwin/PowerDesigner, design dimension/fact tables, role walls and ensure analytics readiness.
Conduct performance reviews of existing data warehouse workloads: identify hotspots, re‑engineer load strategies, improve throughput and scalability across large data volumes.
Mentor junior developers, perform code reviews, transfer knowledge of Teradata utilities, SQL optimisation and data‑warehouse best practices.
Collaborate cross‑functionally with Data Governance, Data Quality, Business Intelligence and Analytics teams to align on data definitions, lineage, metadata and reporting strategy.
Assist in the development and maintenance of test cases, unit tests and regression tests for Teradata codebase and ensure adequate test coverage and validation.

Secondary Functions

Support ad‑hoc data requests from analytics teams, extract or transform data in Teradata for special projects or immediate business needs.
Contribute to the organisation’s data‑warehouse roadmap and strategy: propose migration plans, modernisation, cloud transitions and Teradata enhancement initiatives.
Collaborate with business units to translate new reporting or analytic requirements into Teradata deliverables: new tables, views, ETL workflows or metadata additions.
Participate in agile team ceremonies (sprint planning, backlog grooming, stand‑ups, retrospectives) and help refine technical tasks for Teradata deliverables.

Required Skills & Competencies

Hard Skills (Technical)

Expert proficiency in Teradata SQL (complex joins, analytics functions, OLAP operations) and Teradata utilities (FastLoad, MultiLoad, TPump, BTEQ/TPT).
Strong performance‑tuning skills in Teradata: index design, partitioning, statistics collection, skew analysis, explain plans and query optimisation.
ETL/ELT development skills: designing and implementing pipelines loading large volumes of data into Teradata staging and analytics tables.
Data modelling and data warehousing expertise: creating star/snowflake schemas, dimensional modelling, fact/dimension tables for analytics.
Shell/Unix scripting experience to automate Teradata job scheduling, control flows, batch loads and error‑handling.
Familiarity with scheduling and workload automation tools (e.g., Control‑M, Autosys) and monitoring tools (Teradata Viewpoint, TASM).
Experience with data migration, legacy system integration, data quality processes, profiling and reconciliation within Teradata environments.
Understanding of version control, agile delivery methods, SDLC and DevOps practices applied to data‑warehouse development.
Experience working with large data volumes, scaling architecture and supporting performance at enterprise level (multi‑terabyte systems).
Good documentation and communication skills: ability to author design specs, technical docs, run‑books and convey Teradata technical concepts across teams.

Soft Skills

Analytical and problem‑solving mindset: able to identify root‑causes, debug complex data flows and optimise system performance.
Excellent communication and stakeholder engagement abilities: able to work with business analysts, data architects and management.
Team leadership and mentoring: guide junior developers, promote best practices and foster continuous improvement.
Business‑centric thinking: understand how Teradata data solutions align with organisational goals, analytics and decision support.
Attention to detail and quality orientation: ensure code, data, scripts and integrations are accurate, efficient and maintainable.
Time‑management and prioritisation: able to handle multiple workloads, production support tasks and project delivery deadlines.
Adaptability and continuous learning: stay current with evolving Teradata technology, cloud data architectures, and new analytics demands.
Ownership and accountability: take full responsibility for end‑to‑end Teradata deliverables from requirement to production operation.
Collaboration and cross‑functional teamwork: work effectively within multidisciplinary teams, offshore/on‑shore splits and across time zones.
Resilience under pressure: able to support critical production loads, manage incidents and deliver in fast‑paced enterprise environments.

Education & Experience

Educational Background

Minimum Education:

Bachelor’s degree in Computer Science, Information Systems, Software Engineering or a related technical discipline.

Preferred Education:

Master’s degree or relevant certification in Data Warehousing, Business Intelligence, Teradata or Analytics.

Relevant Fields of Study:

Computer Science
Data Engineering / Analytics
Software Engineering
Information Systems

Experience Requirements

Typical Experience Range:

3‑5 years of hands‑on Teradata development and data‑warehouse experience.

Preferred:

5+ years of advanced Teradata development, large scale data warehousing, performance tuning and leadership responsibilities.