Data Engineer at InvoiceCloud

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

06 Apr, 26

Salary

2.0

Posted On

06 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Data Warehousing, Snowflake, Python, ETL, Data Quality, Data Modeling, Cloud Services, Data Governance, Big Data, Data Pipelines, Data Lifecycle Management, Performance Tuning, Data Analytics, Machine Learning, Data Mining

Industry

Financial Services

Description

About InvoiceCloud: InvoiceCloud is a fast-growing fintech leader recognized with 20 major awards in 2025, including USA TODAY and Boston Globe Top Workplaces, multiple SaaS Awards wins for Best Solution for Finance and FinTech, and national customer service honors from Stevie and the Business Intelligence Group. Judges also highlighted our mission to reduce digital exclusion and restore simplicity and dignity to how people pay for essential services, as well as our leadership in AI maturity and responsible innovation. It’s an award-winning, purpose-driven environment where top talent thrives. To learn more, visit InvoiceCloud.com. Data Warehouse Engineer What a Data Warehouse Engineer should accomplish Design, standardize, and optimize data pipelines connecting all solution area source systems to the enterprise data warehouse. Implement automated, scalable Snowflake development workflows, and ensure the warehouse architecture fully supports advanced data science and analytics initiatives. What does a Data Warehouse Engineer do? Design, administer, develop, and deploy real-time, automated, and scalable data pipelines from multiple source systems into the enterprise data lake and/or data warehouse. Develop and implement auditing, logging, and data quality strategies to ensure reliability, accuracy, and consistency of large-scale data workflows. Diagnose and resolve issues in high-volume data processing systems, ensuring minimal downtime and data integrity. Collaborate closely with technology teams, business stakeholders, and solution area partners to define data requirements and deliver secure, timely access to critical data. Optimize pipeline and query performance using profiling tools, SQL, Python, and other performance tuning methods. Translate operational and analytical requirements into effective data warehouse designs and solutions. Maintain in-depth knowledge of source systems and downstream consumers to champion data quality and usability across the organization. Participate in architecture reviews, contribute to best practice guidelines, and help establish data governance standards. Continuously research and adopt emerging technologies and approaches to improve warehouse performance and scalability. What will I need to thrive in this role? Bachelor’s degree in Data Science, Analytics, Information Management, Computer Science, Information Technology or equivalent professional experience. 3+ years of experience working with SQL in production environments, with strong query writing and optimization skills. 3+ years implementing modern, architecture-based data warehouses in enterprise environments. 2+ years hands-on experience with leading cloud data warehouses such as Snowflake, Redshift, or BigQuery, including familiarity with standard architectural patterns. Proficiency in software engineering and scripting (e.g., Python, Bash, JavaScript) to automate and orchestrate workflows. Ability to communicate complex technical concepts to both technical and non-technical audiences. Strong understanding of data modeling, ETL/ELT design, and data lifecycle management. Proven ability to work with large-scale datasets from diverse data sources. What will give me an advantage in this role? Advanced SQL expertise, including stored procedures, analytic/window functions, and complex query optimization. Advanced Snowflake skills, including streams, tasks, stored procedures, and pipeline orchestration. Experience with cloud-native data services such as AWS SNS, SQS, SES, S3, Lambda, and Glue (or equivalent in Azure/GCP). Familiarity with modern data platforms and orchestration tools such as Apache Airflow, Spark, FiveTran, Kafka, Cassandra, or Elasticsearch. Expertise in data quality frameworks and data governance best practices. Experience working with time-series databases for financial or operational analytics. Background in Big Data, non-relational databases, machine learning, and data mining techniques. Knowledge of security, compliance, and regulatory requirements related to enterprise data storage and usage. Base salary is one component of total compensation. Employees may also be eligible for an annual bonus or commission. Some roles may also be eligible for overtime pay. The above represents the expected base compensation range for this job requisition. Ultimately, in determining your pay, we’ll consider many factors including, but not limited to, skills, experience, qualifications, geographic location, and other job-related factors. Base Compensation Range ₹1—₹2 INR InvoiceCloud is committed to providing equal employment opportunities to all employees and applicants. We do not tolerate discrimination or harassment of any kind based on race, color, religion, age, sex, nationality, disability, genetic information, veteran or military status, sexual orientation, gender identity or expression, or any other characteristic protected under applicable laws. This commitment applies to all aspects of employment, including recruitment, hiring, placement, promotion, termination, layoff, recall, transfer, leave, compensation, and training. If you require a disability-related or religious accommodation during the application or recruitment process, and wish to discuss possible adjustments, please contact jobs@invoicecloud.com. Click here to review InvoiceCloud’s Job Applicant Privacy Policy. For recruitment agencies: InvoiceCloud does not accept unsolicited resumes from agencies. Please do not forward resumes to our job aliases, employees, or any other company location. InvoiceCloud is not responsible for any fees associated with unsolicited submissions.

Responsibilities

The Data Warehouse Engineer will design, standardize, and optimize data pipelines connecting source systems to the enterprise data warehouse. They will also implement automated workflows and ensure the architecture supports advanced data science and analytics initiatives.