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Data engineer

Headquartered in the Silicon Valley with offices in London, Hyderabad and Singapore, Accellor is a Microsoft Gold Partner and a premier Salesforce Partner that uses best-of-breed cloud technology to deliver superior customer engagement and business effectiveness for clients. We bring a deep understanding of Financial, Retail, High Tech, Healthcare, and Retail industries, rolling out end-to-end implementation of salesforce.com and powerful third-party apps. We also build products that are sold on the AppExchange and used by both boutique businesses and Fortune 500 companies.  

Accellor has been honored with the prestigious “Company of the Year” award for "excellence in IT Services" at the Indo Global Business Excellence Awards. Majority of our team members based at Hyderabad, delivering best of breed cloud solutions to customers in the US, UK and APAC region. We’ve created an atmosphere that encourages curiosity, constant learning, and persistence. We encourage our employees to grow and explore their interests. We cultivate an environment of collaboration, autonomy and delegation – we know our people have a strong work ethic and a sense of pride and ownership over their work. They are passionate, eager, and motivated – focused on building the perfect solution but never losing sight of the bigger picture.  

Responsibilities

1. Building a High-Performing Data Platform:

  • Assist in building a data platform to support reporting tools and analytics.
  • Focus on optimising data models for performance.

2. Data Tools Development:

  • Create data tools for analytics and optimise data models.
  • Evaluate and communicate the pros and cons of different modelling approaches.

3. Production Data Pipelines:

  • Design and build production data pipelines within a big data architecture.
  • Utilise continuous delivery practices for deploying, supporting, and operating data pipelines.

4. Understanding of Data Enterprise Applications:

  • Gain a thorough understanding of data enterprise applications such as unified ID, DE-duplication, classification, and aggregation models.
  • Identify and prioritise the source of truth for data.

5. Data Quality Integration:

  • Integrate data quality practices into day-to-day work and the delivery process.
  • Ensure data quality is maintained throughout the data life cycle.

6. Database Experience:

  • Hand on experience in designing database schema covering all use cases
  • Evaluate and suggest suitable database considering pricing and deployment

  • Min 5+ yrs experience as Data Engineer
  • Experience in SQL, Python and PySpark Notebook programming skills. 
  • Need to be able to work through ETL and need to have an understanding of Data Warehousing ETL and reporting. 
  • Exposure to Fabric, Synapse Analytics Notebooks or Databricks is required.
  • Excellent communication and interpersonal skills.
  • Direct Interactions with client
  • Design relational, multidimensional, and Master data management systems

Exciting Projects: We focus on industries like High-Tech, communication, media, healthcare, retail and telecom. Our customer list is full of fantastic global brands and leaders who love what we build for them.

Collaborative Environment: You Can expand your skills by collaborating with a diverse team of highly talented people in an open, laidback environment — or even abroad in one of our global canters.
Work-Life Balance: Accellor prioritizes work-life balance, which is why we offer flexible work schedules, opportunities to work from home, and paid time off and holidays.
Professional Development: Our dedicated Learning & Development team regularly organizes Communication skills training, Stress Management program, professional certifications, and technical and soft skill trainings.
Excellent Benefits: We provide our employees with competitive salaries, family medical insurance, Personal Accident Insurance, Periodic health awareness program, extended maternity leave, annual performance bonuses, and referral bonuses.

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Full-time, remote
DATE POSTED
August 24, 2024

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