Data Engineer Lead dl

🚀 What We Do

• Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.
• Developing scalable data infrastructures, we enhance high-level decision-making, tailored to each client.
• Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.
• Using Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.
• Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.
• Developing recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.

🌟 Our Partnerships

• Amazon Web Services
• Astronomer
• Databricks

🌟 Our Values

• 📊 We are Data Nerds
• 🤗 We are Open Team Players
• 🚀 We Take Ownership
• 🌟 We Have a Positive Mindset
🔍 Curious about what we’re up to? Check out our case studies and dive into our blog post to learn more about our culture and the exciting projects we’re working on! 🚀

Responsibilities 🤓

• Lead end-to-end data migration initiatives, ensuring a smooth, secure, and business-aligned transition.
• Define and communicate data architecture decisions, evaluating impacts, risks, and performance considerations across cloud data platforms such as AWS Redshift, Databricks, and related technologies.
• Coordinate the discovery and documentation of dependencies, schema inventories, data flows, and critical processes involved in migration efforts.
• Own migration and cutover planning, ensuring all activities, validations, and contingency measures are properly defined and executed.
• Serve as the primary liaison between engineering, analytics, product, and business stakeholders, facilitating clear communication and alignment throughout the project lifecycle.
• Translate technical changes in data pipelines, data warehouses, and platform architecture into clear business impact assessments.
• Define and document assumptions, requirements, and acceptance criteria to ensure successful migration outcomes.
• Oversee data validation processes to guarantee the accuracy, consistency, and integrity of migrated datasets against source-of-truth systems.
• Proactively identify, assess, and mitigate migration-related risks, escalating blockers and dependencies when necessary to maintain project timelines and quality standards.
• Drive problem-solving and decision-making in fast-paced, ambiguous environments, helping cross-functional teams stay focused on priorities and deliverables.
• Create, maintain, and improve project documentation, including migration runbooks, testing strategies, rollback plans, and operational procedures.
• Provide regular project status updates to technical and executive stakeholders, ensuring transparency around progress, risks, and next steps.
• Promote data governance, quality, and operational best practices throughout the migration lifecycle.
• Align engineers, analysts, and product stakeholders around priorities, timelines, and delivery expectations to ensure successful project execution.

Required Skills 💻

• Experience in Data Engineering, including building and optimizing data pipelines.
• Experience working with Databricks, Python, and Spark, building batch and streaming.
• Intermediate English Level.
• Familiarity with a BI visualization tool like Looker or Tableau.

🎁 Perks

• Remote-first culture – work from anywhere! 🌍
• AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered
• In-Company English Lessons.
• Birthday off + an extra vacation week (Mutt Week! 🏖️)
• Referral bonuses – help us grow the team & get rewarded!
• Maslow: Monthly credits to spend in our benefits marketplace.
• ✈️🏝️ Annual Mutters' Trip – an unforgettable getaway with the team.
• 👶 Monthly Childcare Reimbursement – Because supporting families matters too

Originally posted on Himalayas